Resilient Rules by ahmad borham

Resilient Rules CULTURE AND COMPLEXITY IN TRADITIONAL BUILT ENVIRONMENTS

Ahmad Borham M.SC. DISSERTATION Arab Academy for Science, Technology and Maritime Transport

ARAB ACADEMY FOR SCIENCE, TECHNOLOGY AND MARITIME TRANSPORT College of Engineering and Technology Department of Architectural Engineering and Environmental Design

RESILIENT RULES Culture and Complexity in Traditional Built Environments By

AHMAD MAHMOUD MANSOUR BORHAM

A thesis submitted to AASTMT in partial

Fulfillment of the requirements for the award of the degree of

MASTER of SCIENCE In

ARCHITECTURAL ENGINEERING and ENVIRONMENTAL DESIGN

Supervisors Lobna A. Sherif

Osama S. Tolba

Professor of Architecture

Associate Professor of Architecture

Arab Academy for Science, Technology and Maritime Transport

Examiners Hisham S. Gabr

Ayman F. Wanas

Professor of Architecture Cairo University

Associate Professor of Architecture Arab Academy for Science, Technology and Maritime Transport Year of graduation 2013

‫األكاديمية العربية للعلوم والتكنولوجيا والنقل البحري‬ ‫كلية الهندسة والتكنولوجيا‬ ‫قسم الهندسة المعمارية والتصميم البيئي ‪-‬القاهرة‬

‫األحكام المرنة‬ ‫الثقافة والتعقد في البيئات المبنية التقليدية‬ ‫اعداد‬ ‫أحمد محمود منصور برهام‬

‫‪AL‬‬

‫رسالة مقدمة لألكاديمية العربية للعلوم والتكنولوجيا والنقل البحري‬ ‫الستكمال متطلبات نيل درجة‬

‫في‬

‫‪FI‬‬

‫‪N‬‬

‫الماجستير‬

‫الهندسة المعمارية والتصميم البيئي‬

‫إشراف‬ ‫أسامة صالح الدين طلبة‬

‫لبنى عبد العظيم شريف‬

‫أستاذ مساعد الهندسة المعمارية‬

‫أستاذ الهندسة المعمارية‬ ‫األكاديمية العربية للعلوم والتكنولوجيا والنقل البحري‬

‫األكاديمية العربية للعلوم والتكنولوجيا والنقل البحري‬

‫الممتحنون‬ ‫أيمن فتح هللا ونس‬

‫هشام شريف جبر‬ ‫أستاذ الهندسة المعمارية‬ ‫جامعة القاهرة‬

‫أستاذ مساعد الهندسة المعمارية‬ ‫األكاديمية العربية للعلوم والتكنولوجيا والنقل البحري‬ ‫سنة التخرج‬ ‫‪2013‬‬

‫إهداء‬

‫إلى أسرتي‬

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‫شكر وتقدير‬

‫هذه الرسالة ما كانت لتتم لوال توجيه وصبر االساتذة المشرفين وتحمسهم لموضوع البحث‪ .‬كما ان االفكار التي احتوت عليها‬ ‫الرسالة قد ازدادت ثراء وتطور من خالل دعم اساتذتي وزمالئي سواء كان ذلك من خالل امدادي بمراجع كانت ركن اساسي في‬ ‫بناء الرسالة او كان ذلك الدعم من خالل تكرمهم بوقتهم في شكل مناقشات مطولة في مناسبات متعددة‪.‬‬

‫‪AL‬‬ ‫‪N‬‬ ‫‪FI‬‬

‫المستخلص‬ ‫تدرس هذه الرسالة تأثير العوامل الثقافية واالجتماعية النابعة من الشريعة اإلسالمية على الطبيعة المركبة‬ ‫للبيئة المبنية التقليدية‪ .‬كانت هذه القواعد تنظم العالقات المجتمعية بما في ذلك األنشطة المتعلقة بعملية البناء في المدينة‬ ‫العربية اإلسالمية‪.‬‬ ‫سوف تحاول الدراسة إظهار كيف كان نظام القواعد التقليدية عامالا رئيسيا ا في مرونة المدينة التقليدية بالنظر‬ ‫للبيئة المبنية على أنها نظام مركب قادر علي التكيف‪ .‬األنظمة المركبة القادرة على التكيف هي أنظمة غير خطية‪ ،‬ذاتية‬ ‫التنظيم لها قدرة على التكيف مع المتغيرات وذلك عن طريق تغيير القواعد المنظمة للتفاعالت التلقائية بين مكونات هذه‬ ‫البيئات‪ .‬هذا التكيف يحدث تدريجيا ا بنا اء على الخبرات المبنية والتي تنعكس على سلوك هذه المكونات‪.‬‬ ‫في محاولة إلثبات هذه الفرضية سوف تحاول هذه الدراسة الربط بين ثالثة مجاالت علمية (نظرية المرونة‪،‬‬ ‫نظرية التعقد وأبحاث البيئة والسلوك) في إطار واحد يهدف إلي بيان أن القواعد المجتمعية المبنية على الفقه اإلسالمي‬ ‫كانت عامال أساسيا في مرونة البيئة المبنية التقليدية‪ .‬هذه العالقات سوف تظهر في صورة رسم بياني أطلق عليه‬ ‫(خريطة القواعد القابلة للحوسبة)‪ .‬يربط هذا الرسم خواص األنظمة المركبة والمرنة بالقواعد التقليدية في شكل يمكن‬ ‫حوسبته‪.‬‬

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‫القواعد التقليدية واألعراف االجتماعية لها طبيعة استشرافية غير مقيدة تحدد المحظور مما ينتج عنه بيئة مبنية‬

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‫مستقلة حيث يكون لقاطنيها القدرة على التحكم في محيطهم‪ ،‬مقارنة بقوانين البناء المعاصرة والتي تميل إلى تقييد‬ ‫تصرفات األطراف ذات المصلحة حسب وصفات غالبا ما تتجاهل احتياجاتهم المتباينة والمتغيرة‪ .‬تطبيق هذه القواعد‬

‫‪FI‬‬

‫يزيد من حرية األطراف المختلفة واستقالليتها كما يقوي الشبكات االجتماعية مما يزيد من مرونة البيئة المبنية‪.‬‬

Declaration

I certify that all the material in this thesis that is not my own work has been identified, and that no material is included for which a degree has previously been conferred on me.

The contents of this thesis reflect my own personal views, and are not necessarily endorsed

by the University.

(Signature) ............................................................................................

(Date) ............................................................................................

Dedication

To my family

Acknowledgments

This work couldn't have been possible except for the guidance, patience of my advisors and their open-mindedness towards the research topic. The ideas discussed in this study has

been really enriched and developed through the support of my teachers and colleagues, whether this was by providing me with references that were essential in building the re-

we had on different occasions.

search argument or by being generous enough with their time to have the long discussions

Abstract This study explores the influence of the socio-cultural rules based upon Islamic jurisprudence (fiqh) on the complexity of the traditional built environment. This system of rules organized the societal activities, including decisions and activities related to design and construction in the Arab-Islamic city.

Considering the city as a complex system, the study will try to show how this rules system made the Arab-Islamic city resilient and adaptive. Complex Adaptive Systems (CAS) are nonlinear, self-organizing systems that have the ability to adapt to changing conditions through changing the rules that organize the random autonomous interactions between agents in the environment. This adaptation takes place through gradual gained experience that is reflected in the behavior of agents.

This study attempts to highlight interrelations between different bodies of literature (resilience theory, Complexity Theory and environment and behavior studies (EBS)) in a sin-

gle framework that aims to show that the resilience of the socio-cultural rules system based

on fiqh was a major factor in the resilience of the traditional built environment. These interrelations are illustrated using a graph called Computational Rules Graph (CRG). The CRG relates the traditional rules system to attributes of complex systems in a graph that can be modeled computationally.

Traditional rules (codes of conduct) are of a proscriptive, non-deterministic nature, defining what is prohibited, thereby producing autonomous environments where agents had control over their immediate environment. In comparison, contemporary rules of the built environment (building codes) tend to be prescriptive (deterministic), subscribing definite actions that need to take place by the stake-holder (agent) neglecting user needs and preferences. The application of these traditional rules systems increased the agentâ&#x20AC;&#x2122;s autonomy and freedom of action. It also helped establish stronger social networks among agents, which resulted in a resilient environment.

iii

Table of Contents Acknowledgments .................................................................................................................. i Abstract ................................................................................................................................. ii Table of Contents ................................................................................................................. iii List of Figures ...................................................................................................................... vi List of Tables........................................................................................................................ vi 1

CHAPTER ONE 1.1

INTRODUCTION...............................1

Research Background .............................................................................................. 2

1.1.1 Resilience ........................................................................................................... 2 1.1.2 Socio-cultural rules ............................................................................................ 3 1.1.3 Complexity and computation ............................................................................. 6 1.2

Research Rationale .................................................................................................. 8

1.2.1 Research problem ............................................................................................... 8 1.2.2 Research questions ........................................................................................... 10 1.2.3 Research objectives .......................................................................................... 11

1.3

Research Structure................................................................................................. 13 RESILIENT SYSTEMS ...................16

CHAPTER TWO 2.1

Introduction ........................................................................................................... 17

2.2

Terminology .......................................................................................................... 18

1.2.4 Research Methodology ..................................................................................... 13

2.2.1 Responsiveness................................................................................................. 18 2.2.2 Resilience ......................................................................................................... 19 2.2.3 Open-endedness ............................................................................................... 19 2.2.4 Adaptability ...................................................................................................... 20 2.2.5 Flexibility ......................................................................................................... 20 2.2.6 Breathing spaces ............................................................................................... 21 2.3

Resilient Systems .................................................................................................. 21

2.3.1 Social networks ................................................................................................ 22 2.3.2 Slow knowledge ............................................................................................... 23 2.3.3 Diversity ........................................................................................................... 24 2.3.4 Redundancy ...................................................................................................... 24 2.3.5 Feedbacks ......................................................................................................... 25 2.3.6 Complexity ....................................................................................................... 25 2.4

Resilience in the Built Environment ..................................................................... 26

2.4.1 Principles of resilient space .............................................................................. 27

iv 2.4.2 Scale and control .............................................................................................. 27 2.4.3 Rules ................................................................................................................. 30 2.5 3

Conclusion............................................................................................................. 31

CHAPTER THREE RESILIENCE IN THE TRADITIONAL RULES SYSTEM ....33 3.1

Introduction ........................................................................................................... 34

3.2

Traditions and Resilience ...................................................................................... 34

3.2.1 Transmission of tradition ................................................................................. 34 3.2.2 Attributes of the traditional .............................................................................. 35 3.2.3 Change and the resilience of traditions ............................................................ 35 3.2.4 Šarīʿah and fiqh ................................................................................................ 36 3.2.5 Change, tradition and continuity: the case of the Arab-Islamic city ................ 38 3.3

Traditional Rules System ...................................................................................... 39

3.3.1 Customs ‘Urf ‫ العرف‬........................................................................................... 41 3.3.2 Inheritance Tawr ̄ith ‫ التوريث‬.............................................................................. 42 3.3.3 Pre-emption Shuf‘ah ‫ الشفعة‬................................................................................ 43 3.3.4 Land revivification Ihy ̄a ‫ إحياء األرض الموات‬....................................................... 44

3.3.5 Principle of damage Ḍarar ‫ الضرر‬..................................................................... 45 3.3.6 Right of precedence Asbaqiya ‫ حق األسبقية‬.......................................................... 46

3.3.7 Servitude Irtifaq ‫ حق االرتفاق‬............................................................................... 46

3.3.8 Right of appropriation of open spaces (Fina’ ‫)فناء‬............................................ 47 3.4

Responsibility and Control .................................................................................... 47

3.5

Conclusion............................................................................................................. 49

CHAPTER FOUR

RESILIENCE IN COMPLEX SYSTEMS ................50

4.1

Introduction ........................................................................................................... 51

4.2

Complexity and Resilience .................................................................................... 51

4.2.1 Complexity ....................................................................................................... 51 4.2.2 Self-organization .............................................................................................. 52 4.3

Complexity in the Built Environment ................................................................... 55

4.3.1 Complexity in social systems ........................................................................... 55 4.3.2 Evolution of Complexity paradigm of cities .................................................... 55 4.3.3 Complexity and the traditional Islamic city ..................................................... 58 4.4

Complex Adaptive Systems (CAS) ....................................................................... 58

4.4.1 CAS and rules................................................................................................... 59 4.4.2 CAS and information ....................................................................................... 61 4.4.3 CAS and identity .............................................................................................. 62 4.4.4 CAS and Scale.................................................................................................. 62

v 4.5

Computational Models of Complex Systems ........................................................ 62

4.5.1 Computational social science ........................................................................... 64 4.5.2 Modeling complexity in the built environment ................................................ 65 4.6 5

Conclusion............................................................................................................. 70

CHAPTER FIVE

THE COMPUTATIONAL RULES GRAPH (CRG) ....72

5.1

Introduction ........................................................................................................... 73

5.2

The Computational Rules Graph (CRG) ............................................................... 75

5.2.1 Red Subgraph ................................................................................................... 78 5.2.2 Blue Subgraph .................................................................................................. 80 5.2.3 Orange Subgraph .............................................................................................. 84 5.2.4 Black Subgraph ................................................................................................ 86 5.2.5 Green Subgraph ................................................................................................ 88 5.3

CHAPTER SIX

CONCLUSION ....................................92

6.1

Summary ............................................................................................................... 93

6.2

Discussion ............................................................................................................. 93

6.3

Future Potential ..................................................................................................... 96

Conclusion............................................................................................................. 90

6.3.1 Traditional and informal settlements ................................................................ 96

6.3.2 Decoding /Encoding rules system .................................................................... 98

6.3.3 Complex adaptive systems (CAS) and governance.......................................... 99 6.3.4 Traditional rules system in domestic context (residential scale) .................... 100 7

Bibliography ................................................................................................................102

List of Tables TABLE 3.1 THE FIVE MAIN LEGAL PRINCIPLES OF FIQH (QAWAÍD FIQHIYYA ‫فقهية‬

‫)قواعد‬, BASED

ON (HAKIM, 2010)................................................................................................................................ 38 TABLE 3.2 SOCIETAL RULES SYSTEM BASED ON FIQH, BASED ON THE WORK OF HAKIM (2008) AND AKBAR (1988A) ............................................................................................................... 40 TABLE 4.1 CHARACTERISTICS OF COMPLEX SYSTEMS AND CAS ACCORDING TO (HAGHANI, 2011) AND (HOLLAND, 1995). ............................................................................................................ 59

List of Figures FIGURE (1.1) AN AERIAL VIEW OF THE URBAN FABRIC IN FEZ (MOROCCO), TAMENTIT (ALGERIA), AND A VILLAGE IN SAUDI ARABIA SHOWING GEOMETRIC COMPLEXITY. SOURCE: (BEN HAMOUCHE 2009A) .................................................................................................4 FIGURE (1.2) SIX EXAMPLES OF TRADITIONAL TOWNS (NOT TO THE SAME SCALE) FROM THE PUGLIA REGION IN THE SOUTHEAST OF THE ITALIAN PENINSULA. THE ITALIAN

URBAN HISTORIAN, ENRICO GUIDONI, MADE A STUDY OF THE ISLAMIC INFLUENCE ON TOWNS IN SICILY AND SOUTHERN ITALY. SOURCE: (HAKIM, 2008) .......................................4

FIGURE (1.3) TWO SIMILAR URBAN FABRICS IN DIFFERENT CONTEXTS A) OBLIQUE AIR PHOTO OF THE CENTRAL PORTION OF FEZ IN MOROCCO B) VERTICAL AIR PHOTO OF A

PORTION OF OLD UNAYZAH, LOCATED IN THE NORTH CENTRAL REGION OF SAUDI ARABIA. THE LARGE BUILDING IS ONE OF THE MOSQUES IN THE CITY, SURROUNDED BY HOUSING. SOURCE: (HAKIM, 1989) ...........................................................................................5 FIGURE (1.4) RESEARCH METHODOLOGY DIAGRAM ......................................................................... 12 FIGURE (1.5) BASIC STRUCTURE OF THE STUDY ................................................................................. 14 FIGURE (2.1) THE ROOM AS AN AUTONOMOUS BUILDING BLOCK. SOURCE (MOUDON, 1986) 27 FIGURE (2.2) FRONT YARDS ARE USED TO ADD ROOMS. SOURCE: (MOUDON, 1986) ................. 28 FIGURE (2.3) ANONYMITY OF SPACE IN QA’A PROTOTYPE. ANONYMOUS SPACES HAVE MINIMAL PREDETERMINED PATTERNS OF USE. THE QA'A PROTOTYPE CAN BE DESCRIBED IN TERMS OF ITS PHYSICAL ORGANIZATION WHICH GIVES IT ITS SPATIAL IDENTITY. THESE SPACES EVOKE QUALITIES THAT ARE MORE THAN FUNCTIONAL, QUALITIES THAT CAN BE DESCRIBED THROUGH ITS PARTICULAR SHAPE, THEIR RELATION TO INSIDE AND OUTSIDE AND TO PUBLIC AND PRIVATE. SOURCE: (HABRAKEN, 1988) .............................................................................................................................. 29 FIGURE (3.1) THE IMPACT OF INHERITANCE ON HYPOTHETICAL URBAN FABRIC. SOURCE: (BEN HAMOUCHE, 2009B) ................................................................................................................. 42

vii FIGURE (3.2) THE IMPACT OF PRE-EMPTION ON HYPOTHETICAL URBAN FABRIC. SOURCE: (BEN HAMOUCHE, 2009B) ................................................................................................................. 43 FIGURE (3.3) IMPACT OF REVIVIFICATION ON HYPOTHETICAL URBAN FABRIC OF THE TRADITIONAL CITY. SOURCE: (BEN HAMOUCHE, 2009B) ........................................................ 44 FIGURE (4.1) COMPLEXITY AS THE DOMAIN BETWEEN ORDER AND CHAOS. SOURCE: (APPELO, 2009) ..................................................................................................................................... 51 FIGURE (4.2) MODELING VS. SIMULATION. SOURCE: (MILLER, 2007) ............................................ 63 FIGURE (4.3) A COMPUTATIONAL MODEL TO SIMULATE SPATIAL STRUCTURES OF MEDITERRANEAN CITIES. SOURCE: (COATES & THUM, 1995) ................................................ 67 FIGURE (4.4) EMERGENT RECURSIVE NETWORKS. SOURCE: (AKBAR, 1988A) ............................. 68 FIGURE (4.5) SETTLING PATTERNS (A) SEQUENCE OF FAVELA OUTPUTS, WITH ATTRACTIVE BOUNDARIES AT THE BOTTOM AND RIGHT SIDE ONLY; (B) DEVELOPMENT PROCESS OF ASHAIMAN SETTLEMENT IN ACERA. SOURCE: (BARROS & SOBREIRA, 2002) .................... 69 FIGURE (4.6) VARIATIONS OF CONSOLIDATION PARAMETERS. DARKEST AREAS ARE THE MOST CONSOLIDATED. SOURCE: (BARROS & SOBREIRA, 2002) ............................................. 69 FIGURE (4.7) PROCESS A&B SHOW EXPERIENCE WITH DIFFERENT INITIAL CONDITIONS

THROUGH ACROSS TIME (T). SOURCE: (BARROS & SOBREIRA, 2002) ................................... 70 FIGURE (5.1) CLUSTER OF NODES CONTAINING THE ATTRIBUTES OF SYSTEMS DISCUSSED IN

THE PREVIOUS CHAPTERS ............................................................................................................... 76

FIGURE (5.2) RED SUBGRAPH WITH ‘URF AS ITS ANCHOR NODE. THE GRAPH DEMONSTRATES THE IMPACT OF ‘URF ON THE DIVERSITY IN THE BUILT ENVIRONMENT. .................................................................................................................................. 77 FIGURE (5.3) BLUE SUBGRAPH WITH INHERITANCE AND PRE-EMPTION AS ANCHOR NODES. THE GRAPH SHOWS THE IMPACT OF THESE ATTRIBUTES IN INCREASING THE COMPLEXITY OF THE BUILT ENVIRONMENT ............................................................................. 79 FIGURE (5.4) CROSSOVER PASSAGES. SOURCE: (HAKIM, 1994) ........................................................ 80 FIGURE (5.5) THE RECURSIVE PROCESS OF SUBDIVISION/AGGREGATION OF PROPERTY IN THE TRADITIONAL URBAN FABRIC OF HAMMET CITY, TUNISIA. SOURCE: (BEN HAMOUCHE, 2009A) ........................................................................................................................... 81 FIGURE (5.6) FRACTAL SIMULATION OF THE SELF-SIMILARITY IN THE STREETS OF CAIRO .. 81 FIGURE (5.7) THE IMPACT OF INHERITANCE OR LAND SUBDIVISION IN ALGIERS ..................... 81 FIGURE (5.8) SELF-SIMILARITY OF QA’A TRADITIONAL DWELLING PROTOTYPE IN TRADITIONAL AL-MEDINA, SAUDI ARABIA ................................................................................ 82 FIGURE (5.9) ORANGE SUBGRAPH WITH ‘RIGHT OF PRECEDENCE’ AS AN ANCHOR NODE. THE GRAPH SHOWS THE IMPACT OF THIS PRINCIPLE ON THE INCREMENTAL CHANGE IN THE BUILT ENVIRONMENT. ........................................................................................................ 83

viii FIGURE (5.10) BLACK SUBGRAPH WITH THE PRINCIPLE OF DAMAGE AS AN ANCHOR NODE. THIS GRAPH SHOWS HOW THIS PRINCIPLE WITH THE AMOUNT OF FREEDOM OF ACTION IT ALLOWED GENERATED COMPLEX BUILT ENVIRONMENT WITHIN A SET OF RULES (COMPLEXITY THROUGH RULES)..................................................................................... 85 FIGURE (5.11) GREEN SUBGRAPH WITH ‘LAND REVIVIFICATION’ AS ANCHOR NODE. THE GRAPH AIM TO SHOW THAT THIS PRINCIPLE ENHANCED THE SOCIAL NETWORKS AND REGULATED THE RESPONSIBILITY PATTERS WITHIN THE BUILT ENVIRONMENT. ......... 87 FIGURE (5.12) THE COMPUTATIONAL RULES GRAPH (CRG), A SUPERIMPOSITION OF THE PREVIOUSLY DISCUSSED SUB-GRAPHS (FIG. 5.2-5.11). ............................................................. 89 FIGURE (6.1) TWO URBAN FABRICS THAT ARE SEPARATED BY OVER NINE HUNDRED YEARS. TOP: BAB AL-WAZIR AREA IN HISTORIC CAIRO (DEVELOPED IN THE ELEVENTH CENTURY); BOTTOM: FUSTAT PLATEAU AREA (DEVELOPED IN THE 1980’S). SOURCE:

(SIMS, 2010) .......................................................................................................................................... 98

CHAPTER ONE INTRODUCTION

"The broader our sample in space and time, the more likely we are to see regularities in apparent chaos, as well as to understand better those differences

that are significant. Thus, the more likely we are to see patterns and relationships,

and these are the most significant things for which to look. Being able to establish the presence of such patterns may help us deal with the problem of constancy and change ...."

(Rapoport, 1979, p. 18)

1.1 Research Background The main idea of this study emerged from an interest in two topics that always seemed in the beginning as parallel: the impact of Islamic law on the urban fabric of the traditional Muslim cities and the application of computer programming in architecture and urban design. Notions of ‘resilience’ and ‘complexity’ brought these two parallel interests together. This research depends on three main concepts: Resilience, socio-cultural rules and Complexity Theory.

1.1.1 Resilience “I wouldn’t design a city, I’d grow one” this is how Bill Hillier1 regards the city as quoted in an article by Philip Ball2 (Ball, 2004) on city. Cities are organic in the sense that they grow, evolve and adapt therefore the current approaches to design must be reconsidered (Ball, 2004).

Resilience is the capacity of a system whether it is an individual, a forest, a city, or an economy to deal with change and continue to develop. It is both about withstanding shocks

and disturbances and using them to catalyze renewal, novelty, and innovation (Folke,

2009). Resilience theory was first introduced by the Canadian ecologist C.S. Holling3 in 1973, whose paper had a substantial impact on understanding the resilience of ecological systems within ecology and other natural and social sciences (Simonsen, 2012).

In resilience theory, systems are understood to be in constant flux, highly unpredictable, and self-organizing with feedbacks across multiple scales in time and space. Among theorists, such systems are known as complex adaptive systems, considered to be the hall-

Bill Hillier is Professor of Architectural and Urban Morphology in the University of London. He presented a general theory of how people relate to space in built environments (Hillier & Hanson, 1984). He is also a pioneer of analysis of spatial patterns known as ‘space syntax’ (Space Syntax, 2012). 2 Philip Ball is the author of “Critical Mass: How One Thing Leads to Another” (William Heinemann, 2004). Applying modern physics models on social and economic phenomena is the main theme of his work (Ball, 2012). 3 Holling has introduced important ideas in the application of ecology and evolution, including resilience, adaptive management, the adaptive cycle, and panarchy (Martinsson, 2007) .

3 mark features of complexity. A key feature of complex adaptive systems is their ability to self-organize along a number of different pathways with possible sudden shifts between states (Folke, 2009).4

During the development of any city, conditions change unexpectedly, which demands a responsive environment. For an environment to be successful, it must adapt to unforeseen changes without the need for major modifications. Anne Vernez Moudon5, in her cross-scale study of neighborhood architecture in San Francisco, calls the space that allows this kind of anticipation ‘breathing space’ (Moudon, 1986). Breathing spaces are a kind of space that permits the unexpected to occur. These spaces have the conditions within that enable residents to interact positively with their environment. The concept of breathing space links different scales from the city through neighborhood and block to the building and the rooms within. Moudon proposes that a main characteristic of breathing spaces is

1.1.2 Socio-cultural rules

‘resilience’ (Moudon, 1986).

The study of socio-cultural aspects comes under what is known as the field of social

science, which refers to the academic disciplines concerned with society and human behavior (Williams, 2000). This field of research includes human geography which focuses largely on the built environment and how space is created, viewed and managed by humans as well as the influence humans have on the space they occupy (Ventura College, 2012). Social sciences also include the study of Law, which is concerned with system of rules based on based on norms accepted by a community, thereby giving these systems an ethical foundation (Hart, 1961).

Complex adaptive systems are discussed in detail in section 4.3 Anne Vernez Moudon’s work focuses on urban form analysis, land monitoring, neighborhood and street design, and non-motorized transportation (UW Landscape Architecture, 2012). 5

Figure (1.1) An Aerial view of the urban fabric in Fez (Morocco), Tamentit (Algeria), and a village in Saudi Arabia showing geometric complexity. Source: (Ben Hamouche 2009a)

Figure (1.2) Six examples of traditional towns (not to the same scale) from the Puglia region in the southeast of the Italian peninsula. The Italian urban historian, Enrico Guidoni, made a study of the Islamic influence on towns in Sicily and southern Italy. Source: (Hakim, 2008)

(a)

(b)

Figure (1.3) Two similar urban fabrics in different contexts a) Oblique air photo of the central portion of Fez in Morocco b) Vertical air photo of a portion of old Unayzah, located in the north central region of Saudi Arabia. The large building is one of the mosques in the city, surrounded by housing. Source: (Hakim, 1989)

Looking at the traditional form of cities, at first glance it seems unordered and cha-

otic and even inappropriate (Fig.1.1-1.3). But this is only because it is incomprehensible to

an outside observer. If we look deeper, we will discover that underneath this unordered surface lies a set of organizing rules that regulate its urban growth. In this sense these urban forms can be regarded chaotic, where chaos is the random-like behavior of a system that is actually determined by a hidden order or pattern. It is suggested that the complexity of these urban forms emerges from few simple rules (Goldstein, 2001). In an interview on the role science can play in designing cities according to rational rules, Bill Hillier says that if we are going to design good cities, we need first to observe them scientifically in order to deduce their fundamental rules (Ball, 2004).

Lawrence (1990) shows that spatial meaning is expressed by unwritten social rules. This explains why the meaning and use of space cannot be prescribed in a deterministic approach. Lawrence continues that if meanings attached to a built environment is to be understood well, our conception of spatial organization should be expanded through exploring the influence of two categories of â&#x20AC;&#x2DC;rulesâ&#x20AC;&#x2122; on the behavior of people: implicit codes (conventions or customs) compared to explicit norms (building regulations). Within this context, the following questions emerge: What are the socio-cultural dynamics used to ex-

6 press the ideas and values of a group of people involved in the design and building process, and what are the physical impacts of these dynamics on the built environment (Lawrence, 1990). Another set of questions emerges: are explicit rules needed at all, and to what extent are they needed (Arida, 2004).

The emphasis on rules may seem contradictory or limiting to the notion of resilience. The notion of rules implicitly indicates rationality, order and determinism, but the lack of rules doesn’t necessarily indicate irrationality and chaos, it can even be possible for rules to produce irrationality (Arida, 2004).

1.1.3 Complexity and computation The bottom-up mindset revolution, started by the efforts of Weaver6 (1948), Jacobs7 (1961), and Holland8 (1995), changed the way we see the world around us and its systems. By the mid 1980’s, this revolution was in full swing. In the field of humanities,

critical theorists, such as Manuel de Landa9, started tackling the concepts of selforganization side by side with the trendy post structuralism paradigm (Johnson, 2001).

Complexity is often adopted by anti-reductionist approaches to science.

Complex systems is a new approach to science that studies how relationships between parts give rise to the collective behavior of a system and how the system interacts and forms relationships with its environment. This approach is also called complex systems

Warren Weaver was an American scientist, mathematician, and science administrator. He is widely recognized as one of the pioneers of machine translation (Yale University Library, 2010). 7 Jane Jacobs was a renowned urbanist, activist and writer. She was best known as a harsh critic of urban renewal, claiming expressways and housing projects destroy diverse older neighborhoods. Her most influential work, The Death and Life of Great American Cities, is a strong critique of the urban renewal policies (Hobart and William Smith Colleges, 2012). 8 Holland has been interested in what are now called complex adaptive systems (CAS). He formulated genetic algorithms, classifier systems, and the Echo models as tools for studying the dynamics of such systems. His books “Hidden Order” and “Emergence” summarize many of his thoughts about complex adaptive systems (Santa Fe Institute, 2012). 9 Manuel De Landa focuses on the theories of the French philosopher Gilles Deleuze as well as modern science, self-organizing matter, artificial life and intelligence, economics, architecture, chaos theory, history of science, nonlinear dynamics, and cellular automata on the other (European Graduate School, 2012).

7 theory, complexity science, study of complex systems, sciences of complexity, nonequilibrium physics, and historical physics.

As complexity results from the interaction between the components of a system, social worlds are complex in the sense that they are composed of multitudes of interconnected elements. Cities are considered by social science as organizational social structures that are changed through various decisions and interactions made through time (Batty, 2007b). Since the 1980’s, there has been a growing trend to consider the city as a complex system, suggesting a radical shift from top-down, centralized management to more decentralized bottom-up structures (Haghani, 2011).

One of the most powerful tools arising from the research in complex systems research is a set of computational techniques that allow a much wider range of models to be explored (Miller, 2007). All complexity theories come with their specific formalism and

models. These complexity models such as CA (cellular automata10), AB (agent-based11), and graph theoretical approaches emphasize bottom-up emergence processes of complex

systems. “[Is] it possible to explain self-organization using more rigorous methods? Can

digital computation be usefully applied to this problem?” (Johnson, 2001). These questions posed by Steven Johnson12 in his book about complexity draws our attention to the possibility that the application of computational models to our understanding of complex adaptive social systems can provide a wider potential for explorations of how these systems begin and grow. Computational social science is a powerful tool for understanding the complexities of real socio-economic systems, by building ‘computational social worlds’ that can be analyzed, experimented with, fed with and tested against empirical data on an unprecedented

Cellular Automata (CA) is a computer simulation method that uses a grid of cells that are governed by certain rules of activity to simulate complexity (Goldstein, 2001). CA will be further elaborated in chapter four. 11 Agent-based modeling is a computer simulation method composed of individuals who act purposely in making locational and spatial decisions (Goldstein, 2001). 12 Steven Berlin Johnson’s work concentrates mainly on the intersection of science, technology and personal experience (Gale, Steven Johnson, 2013).

8 scale. Computational models provide quantitative and qualitative models of social phenomena. One critical application is ‘generative’ explanations. Generative models are an escape from the deductive/ inductive dichotomy. They allow qualitative analysis to be done in a rigorous and controllable way. A typical computational generative approach was proposed by Epstein (1999): first, simple local rules need to be studied and understood. However, generative approaches lead to a great deal of alternative options, all of which are to some extent arbitrary. The construction of plausible generative models is a challenge for the new computational social science as well as a method to avoid ad hoc and arbitrary results. Second, the notion of rules needs clarification and revision. Possibly, rules can be replaced by explicit and theory-founded agent models, which include not only decisionmaking mechanisms but also representations, attitudes, strategies, actions, motivations, and the like (Conte, et al., 2012).

Another crucial idea of computational social science is ‘adaptation’. Social complexity as an emergent phenomenon is caused by successful adaptation. Social complexity

can be caused by uncertainty, which is commonly misunderstood as something that cannot

be known (Conte, et al., 2012). The complex systems approach transpires through and blurs the dividing lines among disciplines and creating a truly interdisciplinary, non-

compartmental science (Conte, et al., 2012).

1.2 Research Rationale The rationale of this research is explained through introducing the research problem, questions, objectives and methodology.

1.2.1 Research problem Jamel Akbar claims that traditional built environments are one of the best physical solutions for users. Hence the processes that generated these forms need to be studied more deeply. He sees that this may bring us closer to a more resilient built environment (Akbar, 1988a, p. 195). Projecting traditions onto the demands of the modern times is not easy, since it may lead to superficial borrowing. In order to connect to our culture an in-depth study of building types is needed from a designers view to understand the design principles behind the type. The purpose of this is not to copy but transform them to be compatible with today's values. Learning from cultural heritage does not mean denying present reali-

9 ties or feature challenges but aims at establishing continuity between the past and the present. Originality is not to refuse the past but to connect to it and transform it to suit contemporary culture to assure continuity (Habraken, 1988).

Lawrence (1987) draws our attention to the fact that, in pre-industrial cultures, architecture is a component of cultural heritage acquired over hundreds of years. Religion, as one of the possible cultural choices, had a significant impact on the house and settlement form in most of pre-industrial cultures (Rapoport, 1969). R. Lawrence (1987) and A. Rapoport (1969) discussed this impact of socio-cultural and religious factors only in the context of primitive communities where religion had a symbolic and ceremonial impact on the built environment. They did not investigate how the principles extracted from religion were the hidden factors behind shaping the traditional built environment.

This study does not depend on religion as the only determinant of the settlements,

cities and house patterns, although religion can have a significant influence on the spatial organization of these patterns in many cultures. Most of the research that studied the im-

pact of religion on the house were a reaction to the common physical deterministic ap-

proach. Considering religion as the single variable affecting the built environment turned these works into anti-physical deterministic nature (Rapoport, 1969).

The works of Amos Rapport (1969), Susan Kent (1993) and Roderick Lawrence (1990) related the studies of ethnography and anthropology to the pre-industrial ‘primitive’ built environments, especially the dwellings. Jamel Akbar (1988a) and Besim Hakim (2008) tried to show how socio-cultural aspect, especially the religion, affected the social interactions and, consequently, the built environments within the context of the traditional Arab-Islamic built environment. The research of Vernez Moudon on Alamo Square in San Francisco (Moudon, 1986) is one of the few studies that mapped the relation between socio-cultural rules and the resilience of the space across time, through many decades and across scale, form the room to the neighborhood. The works of N.J. Habraken (2000) and J. Turner (1977) were amongst the most significant studies to tackle the issue of sociocultural ‘rules’, using the exact terminology, in housing and relate to the issue of ‘responsibility’ and ‘control’. Previously mentioned studies were able to relate just two bodies of literature: environment and behavior studies (EBS) and Resilience Theory.

10 The computational aspect in the work of Hillier and Hanson and their team (Hillier & Hanson, 1984) and (Hanson, Hillier, Rosenberg, & Graham, 1998) is considered the base for dealing with the social aspect based on the work of Kent (1993) and other anthropological and ethnographic research of the built environment. Hillier’s work is mainly analytical and descriptive. Using the results of these analytical methods, some generative research was conducted by Adam Doulgerakis (2007) incorporating genetic programming tools. Implementing a genetic component to the software can help it to incorporate proscriptive generative rules, which were studied in the work of Akbar (1988a), Hakim (2010) and Moudon (1986).

Another significant research is the work of Carl Bovil (1996) on fractals13 at the architectural scale, especially the vernacular, and the work of Michael Batty (Batty & Longely, 1994) at the city scale. These aforementioned studies have related Complexity Theory to the environment and behavior studies (EBS). This relation has been further studied in the works of M. Ben Hamouche (2009b), theoretically and applied in the work of

Paul Coates (Coates & Thum, 1995) that was demonstrated under the title ‘Islamic City

Algorithm’.

1.2.2 Research questions

The study aims to investigate the resilience of the traditional rules system based on Islamic law through establishing a relationship between it and the notions of selforganization and emergence that are based on Complexity Theory. Considering the city as a complex system, the study will try to show how these rules system made the ArabIslamic city resilient and adaptive. In order to achieve this aim, the study at hand attempts to answer the following questions:



Can the built environment be interpreted through the resilience theory?



What is the influence of socio-cultural rules on the built environment?



What makes cities complex social systems?

Fractals are geometric patterns, structures that are self-similar at multiple scales (Goldstein, 2001).

11 

What are the manifestations of self-organization and emergence in the traditional built environments?

By establishing this framework, the study aims to show the resilience of the traditional rules system by relating it to the notions of self-organization and emergence based on Complexity Theory.

1.2.3 Research objectives In the course of the following study the following objectives will be fulfilled:  Identify the factors of resilience in the built environment from previous research.  Demonstrate the influence of socio-cultural rules system on the traditional built environments.  Establishing a relation between resilience of traditional built environment and

socio-cultural rules system.  Examining the complexity of the traditional built environments.

 Establishing a relation between the traditional rules system and the complexi-

ty of the traditional environment.

Figure (1.4) Research methodology Diagram

1.2.4 Research Methodology The study will try to reach its aims and objectives through content-analysis, interpretation and interrelating different fields of literature (resilient theory, environment and behavior studies (EBS) and Complexity Theory) to identify patterns that may reveal a theoretical framework. These different bodies of literature are analyzed through the tracing of a number of concepts such as scale, control, responsibility and rules (Fig.1.4). This process leads to the basic relation which is shown in the basic structure of the study (Fig. 1.5). This framework will be further verified in the form of a graph that maps the connections between these fields. This graph will be dubbed as â&#x20AC;&#x2DC;Computational Rules Graphâ&#x20AC;&#x2122; (CRG). The built environment will be studied from three perspectives based on the following systems: resilience systems (resilience theory), traditional rules system (EBS), and complex systems (Complexity Theory). The investigation unfolds in three steps: 1. Claiming that traditional built environment is a complex system 2. Showing that complex systems are resilient by interrelating them to the

attributes of resilient systems.

3. Relating the traditional rules system to both complex and resilient systems,

showing that this rules system was an attribute in the complexity of the

traditional built environment and thus a factor of its resilience.

1.3 Research Structure As a general structure, shown in Figure 1.5, this study consists of six chapters. Three core chapters trace the notion of resilience in the systems mentioned above in a consistent manner. First, the system is introduced, then its main characteristics are discussed and, finally, its relation to the built environments is demonstrated. Then these chapters are followed by a chapter were the interrelations between these systems are discussed.

Chapter one introduces the background, motivations of the research and the main concepts to elaborated on in the course of the study. It then lists the objectives and the aims of the study and mentions the methodology to achieve them. Chapter two discusses the concept of resilience, which is distinguished from similar terms such as flexibility and adaptation. It also discusses resilient systems and their characteristics. The chapter the

Figure (1.5) Basic structure of the study

15 introduces the next chapter by showing how built environments (in general) can be resilient and explains the concept of the breathing space. Chapter three discusses the resilience of the traditional built environments. It also explains the concept of â&#x20AC;&#x2DC;the traditional rules systemâ&#x20AC;&#x2122; that governed the social interactions in Arab-Islamic cities. Chapter four discusses the resilience of complex systems. It defines complex adaptive systems and discusses its characteristics. It introduces the Complexity Theory of Cities (CTC). It takes this theory as a base to explain the complexity of the traditional built environment. Chapter five attempts to establish a relationship between the systems discussed in the preceding chapters. The relations are mapped in the form of a graph that will be referred to as Computational Rules Graph (CRG). These relations are verified and supported using three interrelated bodies of literature (Complexity Theory, Resilient Systems and environment and behavior studies).

Finally, chapter six shows how the methodology of content-analysis and interpretation used in the research supports the hypothesis that the traditional rules system is a factor in the resilience of the Arab-Islamic traditional built environments due to self-regulating

and proscriptive nature. The chapter also discusses the future research potentials in explor-

ing the following: similarities between traditional built environments and contemporary spontaneous settlements (informal settlements), complex adaptive systems paradigm in

governance, and socio-cultural rules at the domestic scale.

CHAPTER TWO

RESILIENT SYSTEMS

“Resilience balances continuity and change in space”

(Moudon, 1986, p. 157)

2.1 Introduction “Where change is perceptible, rapid change makes change itself even more visible. Velocity becomes a concrete condition, not just a measure of speed. Rapid change in cities has highly legible moments—the material reality of buildings, transport systems, re-placements of modest shops with luxury shops and of modes middle-classes with the rich professional class, a bike-path where there was none— and they can be both good and not so good. Further, when rapid transformation happens simultaneously in several cities with at least some comparable conditions, it also makes visible how diverse the spatial outcomes can be even when the underlying dynamics might be quite similar. All of this brings to the fore the differing degrees of openness of cities. I prefer thinking of this as the incompleteness of cities, which means that they can constantly be remade, for better or for worse. It is this incompleteness that has allowed some of the world's great old cities to outlast kingdoms, empires, nation-states and powerful firms.”

(Sassen, 2011, p. 2)

The built environment needs to be responsive in the face of unexpected changing

conditions whether quantifiable (climatic, technical, economic, demographic) or latent and non-quantifiable (social, cultural). This shows the need for a flexible built environment that is supportive to accommodate both synchronic diversity and diachronic change (Rapoport, 1990).

It is important to note that the quality and rate of change within traditional built environments has greatly differed compared to contemporary ones. Conditions of cultural stability, social homogeneity and slow rate of technological advancement characterized the traditional built environment as opposed to the contemporary impact of infrastructure and rapid urbanization rates. Despite of this fact, studying the factors that made these environments adaptive to various types of change can be valuable in dealing with contemporary conditions.

Amos Rapoport states that a principle reason for flexibility and open-endedness is to maximize the user’s choice that allows for diversity and change of life. He explains that choice and transformation are the most ‘traditional’ way to achieve congruence, which he

18 defines as the usersâ&#x20AC;&#x2122; ability to design and shape the surrounding environment without questioning group norms (Rapoport, 1990).

2.2 Terminology There are many terms found in the literature of the built environment dealing with change such as open-endedness, responsiveness, resilience, adaptability, and flexibility. Rapoport tries to answer the question whether these terms are synonyms for a single notion or a variety of notions (Rapoport, 1990). In the following sections, these terms will be further explained.

2.2.1 Responsiveness Responsiveness refers to the possibility of a given design to respond to the variability and diversity of cultures and changes of cultures over time. It is the ability to become congruent with culture (Rapoport, 1990). Another definition is provided by Rapoport for

responsiveness is when environment can be manipulated as cultures change. He also dubs

it as supportive environments (Rapoport, 1984).

Rapoport draws our attention to important issues such as for whose culture environments should be responsiveness and which elements of it should be responsive. He mentions some cultural mechanisms, such as technical aspects of activities, meaning, identity, tradition and continuity, that link people to their environments which make it more responsive. According to Rapoport, maximizing choice is critical in this process of being responsive (Rapoport, 1984).

Rapoport states that traditional built environments were more responsive to the culture of their users. He sees that this was mainly because these environments â&#x20AC;&#x2DC;communicatedâ&#x20AC;&#x2122; effectively with those users. This can still be evident in contemporary spontaneous and

19 popular settlements1. This is why these environments can be a valuable source for learning about responsiveness (Rapoport, 1984).

2.2.2 Resilience “Resilience balances continuity and change in space” (Moudon, 1986, p. 157)

Moudon used the term ‘resilience’ in relation to the built environment and defined it as "the ability of space to assume a variety of functions as well as meanings, to be owned and inhabited in a variety of ways without major disruption of the structure of space. This resilience that Moudon refers to is the unexploited potential of the space. What is significant in this term, as it is defined here, is that it can apply to all and any scale in the urban space, as Moudon claims (Rapoport, 1990).

Resilience is the capacity of a system whether it is an individual, a forest, a city, or an

economy to deal with change and continue to develop. It is both about withstanding shocks and disturbances and using them to catalyze renewal, novelty, and innovation (Folke,

2009). Cities show resilience against exerted forces to different extents and in different

ways. It is the mechanisms of urban growth that ensure the stability of the city where hierarchical differentiations is associated with building resilient systems (Batty & Longely, 1994).

2.2.3 Open-endedness A general definition of ‘open-endedness’ can be “the overall capacity to accommodate a wide range of user needs at one time or over time” (Rapoport, 1990). It was also suggested in an attempt to reconcile the term resilience with open-endedness, that resilience is open-endedness in addition to control (Rapoport, 1990). Resilience and openendedness also involves the aspect of choice. Users have to be willing and conscious of the

The notion of the resilience of spontaneous settlements will be further discussed in the last chapter of this study.

20 potential open-endedness in order for it to become actual open-endedness (Rapoport, 1990).

Rapoport uses the term ‘open-endedness’ to refer to the ability of individuals to exert some control over the environment. It is the ability of the environment to respond to diversity synchronically and to change diachronically. It addresses both latent and instrumental aspects. He also refers to this ability as ‘loose-fit’ in correspondence to ‘Breathing Space’ in Moudon (1986). Rapoport consider this the most general term that subsumes the other terms (Rapoport, 1990). He shows that open-endedness in the built environment can be found in different forms at different scales from a room to a whole settlement.

2.2.4 Adaptability Adaptability is defined as the ability to serve a number of different functions over a period of time. This definition that is based on Pikusa’s2 research, neglects synchronic di-

versity. It also focuses much on functional aspect of change while neglecting change in

2.2.5 Flexibility

meaning (Rapoport, 1990).

Based on Oxman’s3 work, Rapoport defines flexibility as the ability of a system to support variation or being different in such a manner that suites the function in the face of changing conditions. It is the ability to adjust to change while maintaining stability in other qualities (Rapoport, 1990). This definition is similar in essence to the notion of resilience as defined by Moudon (1986). Similar to Pikusa’s definition of adaptability, it neglects diversity at a specific moment of time.

Stefan Pikusa studied adaptability and dwelling principles in the Australian house in most of his publications such as “The Adelaide House 1836 to 1901, the evolution of principal dwelling types” 3 Rivka Oxman research focused on models of design thinking and design computation. Her current research relates to the contribution of digital media and technologies to the emergence of digital design models and paradigms (GSD Harvad University, 2013).

21 Rapoport provides an overview of these terms and how they are used, either independently or simultaneously. Looking back at the definitions mentioned earlier, he sees that open-endedness and responsiveness are the broadest and most general terms that capture the ability of environments to cope with diversity, variability and change. He sees that all the other terms: adaptability, flexibility and resilience, refer to different ways of achieving open-endedness (Rapoport, 1990). Also he mentions that open-endedness or resilience can be achieved through adaptability or flexibility.

2.2.6 Breathing spaces ‘Breathing spaces’ are spaces that permit the unexpected to occur. These spaces have the conditions where residents are able to interact positively with their environment. These spaces provide the conditions for city residents to positively interact with their environments. The concept of breathing space links different scales from the city through neighborhood and block to the building and the rooms within. Several terms that are simi-

lar to the concept of breathing space were previously introduced in many literatures such as the work of John F.C. Turner and it was also referred to by Rapoport as ‘loose fit’

2.3 Resilient Systems

silience’ (Moudon, 1986).

(Rapoport, 1990). Moudon proposes that the main characteristic of breathing spaces is ‘re-

Resilience thinking is system thinking: it provides a framework to understand socio-ecological systems. It’s about seeing systems as a whole that operates across different scales in time and space. This framework of understanding puts into consideration linkages between components of the system, thresholds between states of equilibrium4, and adaptive cycles. It’s about understanding and embracing change and adaptability, as opposed to striving for constancy and control (Walker & Salt, 2006). Three imperative concepts to this paradigm are suggested by Walker and Salt (Walker & Salt, 2006):

Equilibrium indicates rest state of a dynamic system (Goldstein, 2001).

22  We are all part of social systems that are highly interconnected.  Socio-ecological systems are complex adaptive systems that behave in a nonlinear and unpredictable manner.  These systems are resilient.

The physical definition of resilience is the ability of a material to accept large deflection without damage where deflection is limited either by yield (permanent deformation) or by fracture (Ashby & Johnson, 2002). From system perspective, resilience is “the capacity of a system to absorb and utilize or even benefit from perturbations and changes that attain it and to persist without a qualitative change in the system's structure” (Van der Leeuw & Leygonie, 2000, p. 9).

A system can be called ‘resilient’ when it operates in such a way that it can utilize its potential abilities to the maximum possible extent in a controlled manner, either in ex-

pected or unexpected situations (Hollnagel, Woods, & Leveson, 2006). Following are some of the main characteristics of resilient systems branching from the three main concepts

previously mentioned and based on Wildavsky5 work (Pelling, 2003): social networks,

2.3.1 Social networks

slow knowledge, diversity, redundancy, tight feedbacks and complexity.

We live and operate within socio-ecological systems where social systems are inextricably linked with the ecological systems in which they are embedded (Walker & Salt, 2006). The faster the flow or resources through a system, the more it will be able to cope with perturbation. Overly hierarchical systems hinder such flow.

Aaron Wildavsky was an American political scientist known for his pioneering work in public policy, government budgeting, and risk management. “Searching for Safety” is one of his important publications on the concept of resilient systems (Gale, 2003).

23 A set of linked hierarchies in mesh-like structure can better govern the behavior of a system. This linked set of hierarchies is referred to as ‘panarchy’6. This linkage across scales is a key aspect of adaptive cycles of a system (Walker & Salt, 2006). Thus top-heavy systems are less resilient (Pelling, 2003). Information in the city should be allowed to flow freely between experts, policy-makers and citizens. Local knowledge and development priorities need to be identified and risks must be clearly communicated (Pelling, 2003). A resilient environment would promote well-developed social networks and adaptability (Walker & Salt, 2006). Resilience in socio-ecological systems is very strongly connected to the capacity of the people in a system to respond, collectively and effectively.

2.3.2 Slow knowledge Slow knowledge can defined as the experiences built over time and earned by trial and error, such as traditions that are handed down from generation to another. This incremental accumulation of knowledge preserves the connective patterns within. Thus complex

and resilient environments emerge from slow knowledge (Orr, 2002).

Multi-scale socio-ecological systems involve multiple interacting variables. These

interactions are of a dynamic nature, crossing scales between human and natural systems. Increasing the resilience of a system is all about understanding the variables that cause it to cross thresholds between different states of equilibrium. Thresholds can be considered as levels in controlling slow variables (Walker & Salt, 2006). A resilient environment would have a policy focus on the ‘slow’ variables of the system such as population growth or climatic change (Walker & Salt, 2006).

Attributes such as small scale, slow population growth and slow change have many direct and indirect effects on the built environments such as conflict-resolution and privacy mechanisms. It also has an impact on social networks and interaction and communication

Panarchy is a term coined by C.S. Holling and Lance Gunderson to describe cross-scale interactions among systems (Harrell, 2011).

24 between agents. All these changes have a strong impact on the settlement form and thus on the whole built environment (Rapoport, 1989).

2.3.3 Diversity Risks are greatest when functions are dependent upon a single resource. Diversity of resources supports resilience at local levels (Pelling, 2003). Variety of resources and the means of their flow across the system can provide compensation through alternatives in the case of some other resources failure (Pelling, 2003).

A resilient system promotes and sustains diversity in all forms, for a diverse heterogeneous entity can adapt to a constantly changing world, without fatal crushing of its structure. A diverse structure can speed up the adaptation capacity of a system, increasing its resilience (Haghani, 2011). A resilient environment would embrace diversity and variabil-

2.3.4 Redundancy

ity rather than attempting to control and reduce it (Walker & Salt, 2006).

In information theory, redundancy is the repetition in patterns of a message in a

communicational channel. Thus, it can be defined as the existence of repetitive patterns or structures (Goldstein, 2001). Overlapping of functions in a system allows it to adapt to change where critical functions continue to perform while other redundant elements take over new ones (Pelling, 2003). Complex systems demand a certain amount of redundancy in order to reach a stable state. Novel patterns result from recombination of redundant patterns (Goldstein, 2001).

As societies grow larger in scale and less homogeneous, environments communicate less effectively. These societies have more diverse components and as a result they require more redundancy in the ways of communication (Rapoport, 1989). This is further supported by a stronger influence of rules, customs and social norms, which occur in traditional settings.

Resilient social-ecological systems have many overlapping ways of responding to a changing world. A resilient environment would have institutions that include â&#x20AC;&#x2DC;redundancyâ&#x20AC;&#x2122; in their governance structures and a mix of common and private property with overlapping

25 access rights. Pure top-down governance structures with no redundancy in roles may be efficient in the short term, but they tend to fail when the circumstances, under which they were developed, suddenly change. More ‘messy’ structures perform better during such times of change (Walker & Salt, 2006).

2.3.5 Feedbacks Feedbacks can be considered as the secondary effect of one variable on another. Positive feedback enhances that effect while negative feedback reduces it (Walker & Salt, 2006). Feedbacks maintain interactions between different components of a system by signaling change and enabling learning building up knowledge from experiences. Thus resilience of systems is enhanced when feedbacks are effectively transmitted (Pelling, 2003).

Maintaining feedback loops is a key principle in the resilience of socio-ecological systems. These loops allow the detection of thresholds between different states of equilib-

rium. Creating strong feedback loops is critical in supporting the resilience of systems, especially complex ones (Walker & Salt, 2006). For example, local participation in decision-

making through formal democratic structures and involvement in local development pro-

jects will maximize the benefit gained by citizens from development programs and projects (Pelling, 2003). Unfortunately, feedback loops are getting looser at all scales in a globalized world (Walker & Salt, 2006).

2.3.6 Complexity It is claimed that social-ecological systems are complex adaptive systems7. This is mainly because they do not change in a predictable, linear fashion. In addition, they have the potential to exist in more than one kind of stable states (this is referred to as ‘alternate stable states’), in which their function, structure, and feedbacks are different. The complexity of the many interconnections and interactions that make up a social-ecological system is

Complex adaptive systems will be further explained in chapter 4.

26 what makes it difficult to predict with certainty the exact response to any intervention in the system (Walker & Salt, 2006).

Complex adaptive systems have â&#x20AC;&#x2DC;emergentâ&#x20AC;&#x2122; behavior. This quality of emergence shows the inadequacy of understanding socio-ecological systems by only studying a pair of interactions in isolation of the rest of the system. Emerging results from studying complex systems demonstrate that changes in one component can significantly affect the whole configurations of the system; it can make the system shift to a different stable state (Walker & Salt, 2006).

The resilience of socio-ecological systems is greatly enhanced when its complexity is managed through a network of stakeholders from different levels of the society. This dynamic structure allows for cross-scale feedbacks, thereby enhancing passing experiences across the network for problems solving. This hand-over of experiences creates diversity of

experiences and simulates innovations that are further circulated across feedback loops

across different scales (Walker & Salt, 2006).

2.4 Resilience in the Built Environment The process where the city takes form can be seen as series of negotiations between what exists and what is new (Moudon, 1986). Neighborhood fabric is gradually modified. This shows that change is incremental in nature. Change and transformation occurs at the scale of the lot as it is the basic cell of the neighborhood, and eventually the city also changes. As cells, lots are responsible for the emergence of the pattern of the grain of the city and determining its scale. Consequently, grain and scale define who controls which territory of the city (Moudon, 1986). The smaller the increment of land ownership, the more the diversity created in the environment. Lot size has an influence on the rebuilding rate of the city. As smaller lots are cheaper they are more accessible to a greater portion of the population (Moudon, 1986).

Needs and preferences of users that come with their activities and available technologies and standards must to be accommodated by a built environment that is resilient, adaptable and responsive to the previous through certain mechanisms and rules, systems (Rapoport, 1990).

2.4.1 Principles of resilient space As previously mentioned, Moudon (1986) defines resilience in the built environment as the ability of space to assume a variety of functions and meanings and to be used in different ways without a major rupture in its structure. Resilient space, as Moudon (1986) sees it can be reinterpreted and used in a variety of ways while keeping most of its original shape. It should provide inhabitants with a great deal of control over what can be done with space without modification. Moudon (1986) mentions two simple and straightforward principles that can increase the resilience of space: under-design and generous space dimensions.

 Under-design Regardless of the scale whether it is a city or a building, Moudon (1986) sees that it is essential not to design everything, which is supported by Rapoport term ‘under-design’ (Rapoport,

1990). Under-design, not only gives a margin for the personalization of the space, but also gives a

margin for the space to be able to accommodate the future unexpected uses.

 Generous space dimensions

Moudon (1986) states another principle for increasing resilience of space is the use of generous space dimensions, but within the limits

Each space is autonomous. Rooms have their own fenestration and independent access. The hallway is reserved as permanent access space to rooms, although it can also house other functions.

Zones of ambiguity are created as each room may expand into adjacent spaces through often large doorways.

that enable the users control over the space and manipulating it to suite their activities.

2.4.2 Scale and control Through Moudon’s study of neighborhood architecture in San Francisco (Moudon, 1986), she demonstrates how the principles of resilient space are applicable on different scales: city scale

Three possible combinations of rooms on one floor: a. combining the front and one middle room; b. combining the two middle rooms; c. combining all rooms.

and building scale. Figure (2.1) The room as an autonomous building block. Source (Moudon, 1986)

ď&#x201A;ˇ Building scale: The room as building block At the building scale, Moudon suggests that it is essential to return to the room as the module in designing a resilient space (Moudon, 1986). For her, using the room as a generic module requires that furniture and equipment not to be the determinant of the room size. She sees that the value and characteristics of separate circulation space to support the changing and various use of rooms within the building needs to be re-considered (Moudon, 1986). Rooms are valuable for their multi-purposeness. This can be due to their regularity in shape and flexibility in size (Fig. 2.1).

Open spaces such as terraces, roof spaces and attics are of high value especially in dense urban fabric. Such unfinished spaces are essential to the response of the building to change over time. These

spaces provide potential adaptability at the building scale by extendibility and improvements

(Rapoport,

incremental

1990). Also open-endedness at the dwelling scale includes open spaces that surround the house including streets and other dwellings. An example of this from Moudonâ&#x20AC;&#x2122;s study of one San Francisco neighborhoods is shown in Figure 2.2.

Figure (2.2) Front yards are used to add rooms. Source: (Moudon, 1986)

Anonymity, as opposed to specificity, is another aspect that can support resilience at the building scale. Anonymous spaces have minimal predetermined patterns of use (under-determination vs. over-determination). In other words, they are spaces that can be interpreted and used in multiple ways and have minimum design features that may limit user choices (Rapoport, 1990).

An example of this anonymity of space can be found in the traditional house type across Arab-Islamic cities. In this house typology, the relation between space and function is much more complex than in the modernist house designs, where spaces of the house are

29 designed and named after their intended functions regardless of the activities they may host. In traditional houses, the identity of typological spaces such as the Qa'a8 (Fig. 2.3) is not derived from the activities that take place in them, but from their position within the spatial system. Therefore, the Qa'a prototype can be described in terms of its physical organization which gives it its spatial identity. These spaces evoke qualities that are more than functional, qualities that can be described through its particular shape, their relation to

inside and outside and to public and private (Habraken, 1988).

Figure (2.3) Anonymity of space in Qa’a prototype. Anonymous spaces have minimal predetermined patterns of use. The Qa'a prototype can be described in terms of its physical organization which gives it its spatial identity. These spaces evoke qualities that are more than functional, qualities that can be described through its particular shape, their relation to inside and outside and to public and private. Source: (Habraken, 1988)

The qa’a is a room with the following plan: two elevated areas (iwans) opposing each other and overlooking a lower area called the durqa‘a. The plan was inspired from the four-iwan plan or cruciform plan of the religious buildings. They were found in houses on ground floors and first floors alike. (Thesaurus Islamicus Foundation, 2006). 8

ď&#x201A;ˇ Urban scale It can be useful in tracing change and transformation within the built environments if lots are considered as the basic cell of the neighborhood fabric. Lot size influences the pattern, grain and scale of the city. This cellular character of lots relates the urban scale to the architecture (Moudon, 1986).

At the urban scale, fine-grained urban fabric that consists of small lots helps to increase the urban resilience, as small lots result in more buildings; this encourages more interactions between individuals. This kind of fabric slows down the rate of change and thus limits the real estate large scale interventions (Rapoport, 1990). Distributed ownership over multiple small lots not only provides residents with a high level of control, but also results in diversity and variety, hence the resilience of the built environment (Moudon, 1986). In the case of Alamo Square in San Francisco, as the scale of the lots changed and the ownership was disassociated from the actual residents, their needs no longer found a physical

resolution in the built environment (Moudon, 1986).

Habraken sees that to use a built form is to exercise some control to be able to

transform (Habraken, 2000). Whoever controls whatsoever territory in the city has significant repercussions on both city and building design scale (Moudon, 1986). Resilient space provides its users with control over it. This control should be direct and simple. The inhabitant controls the building internally, and maintains it and can determine its use. This inhabitant can also easily control the use of the immediate outdoor private space adjacent to the house. This control occurs incrementally within the scale, which Moudon calls â&#x20AC;&#x153;City residential cellâ&#x20AC;?. This cell includes the lot(s), the building(s), and the dwelling(s). Control can be exercised through the life cycle of the cell through design, building, usage/maintenance, transformation, demolishing or replacement (Moudon, 1986).

2.4.3 Rules Moudon speaks of tight rules that governed land subdivision and house design and construction. These rules belonged to traditions that were either already commonly used in the city or had been agreed upon among residents (Moudon, 1986). These traditions played an important role in shaping the city and its elements such as streets, blocks and buildings. Traditions, in this sense, can be regarded as a guiding design and planning activities in the

31 city. Within this framework of rules, the builder had the freedom to make a series of choices (Moudon, 1986). Thus an accretion of decisions resulted in diverse solutions. A similar result is mentioned by Akbar in the context of the Arab-Islamic traditional city, where a complete freedom was offered to builders within environments regarded as a set of constraints (Akbar, 1988b).

There are two dimensions of the built environment that can be identified in the work of Moudon (Moudon, 1986). The first is physical elements (spatial patterns), while the second is the ‘rules’ that govern these patterns or elements. Physical elements of different scales such as the grid, the houses and the rooms form together the urban built environment. Moudon attempts to relate these physical elements at various scales (Moudon, 1986).

The ‘spatial structure’ is a concept that was used by Moudon to explain the physical

characteristics of environments shaped by a succession of traditions. This concept also helps to distinguish between the physical elements of space and the rules that organize the

assembly of several elements whether similar or different in scale (Moudon, 1986). Both

physical elements and rules change over time. It is possible that the same physical element such as a house responds to a different set of rules through different periods of time, or two elements of different scale and age are related according to the same set of rules. Rules also can be based on different kinds of logic.

The interaction between elements and rules opens up a number of possibilities in dealing with the notion of order and variety within the built environment (Moudon, 1986). Diversity is attributable to traditions (Moudon, 1986), yet traditions form a unifying agent that restrains variety (Hakim, 1994). Moudon considers traditions as a framework of rules that guides design and building activities, but she also emphasizes that traditions are not laws.

2.5 Conclusion The chapter introduced the choice of resilience as a focus of the study with a distinction between different terminologies used to refer to how environments deal with

32 change such as open-endedness, responsiveness, resilience, adaptability, and flexibility. The notion of resilience were discussed in relation to the built environment.

The paradigm of resilience is built mainly upon the three concepts of interconnectedness, complexity and resilience. Since this paradigm is system related, the main characteristics of resilient systems were further explained.

Resilience in the built environment is closely associated with the incremental nature of change. Some principles such as under-design and generous dimensions of space can enhance the resilience across scales. Implications of the scale in the built environment on the issue of control were further demonstrated. The notion of rules that organize building and design activities has been discussed in relation to traditions. The notion of traditions

will be further elaborated on in the next chapter.

CHAPTER THREE

RESILIENCE IN THE TRADITIONAL RULES SYSTEM

“It is the very looseness of the Muslim City that gave it resilience….. It is Islam that gave the Muslim city its resilience.”

(Grabar, 2006, p. 174)

3.1 Introduction Tradition is defined in the Concise Oxford Dictionary (Oxford Dictionaries, 2010) as: “a long-established custom or belief that has been passed on from one generation to another”. The term is used un-consciously contrasting modernization but it is much more complex than this. The term implies: rural in contrast to urban, old (something that belongs to the past), and this can be pre-literate, pre-colonial, pre-independence, or pre-industrial (Rapoport, 1989). The term ‘tradition’ can have a positive or a negative connotation, where the latter being more common. It can be a neutral one as well. The concept of tradition is not rejected all the way. It is possible, in some cases, that traditional artifacts can be admired while the traditions behind their production are rejected (Rapoport, 1989).

3.2 Traditions and Resilience In this section the relation between the notions of traditions and resilience will be

discussed from different aspects including its relation to Islamic law (Šarīʿah ‫)شريعة‬.

3.2.1 Transmission of tradition

"In all the great cultural undertakings of the human race, the oral transmis-

sion of tradition plays a great role”

Edward Shils1 cited in (Tuan, 1989)

Transmission is the essence of tradition (Bourdier, 1989). Tradition would be knowledge transmitted, handed down or passed on what is of value, whether through speech, writing or drawing (Bourdier, 1989). Establishment and maintenance of tradition requires the passing of its essential elements from members of a group to their successors. There can be different kinds of traditions since anything can become a tradition by being transmitted over time (Rapoport, 1989). Transmission can be through different mechanisms

Edward Shils was known for his research on the role of intellectuals and their relations to power and public policy (University of Chicago, 1995)

35 but it always involves people. Only people are capable of translating schemata and patterns into built form (Rapoport, 1989).

3.2.2 Attributes of the traditional For the traditional, vernacular, historical environments to be studied and learnt from, it is essential to study and analyze them in terms of concepts, and derive lessons that are applicable to research, theory-building or design. Learning from tradition can be in different ways that are all valuable. It can be about specifics, process or characteristics of a product.

The term â&#x20AC;&#x2DC;traditionalâ&#x20AC;&#x2122; has different connotations in general and specifically in connection with the built environments. To clarify these concepts a large number of attributes or characteristics need to be defined (Rapoport, 1989). Rapoport sees that no single attribute or characteristic is sufficient to define the complex concepts of tradition or traditional.

This is done through content-analysis of literature.

Tradition is a general concept that applies to a wide range of domains. It is then

necessary to relate the general attributes of tradition to traditional built environments. Traditional Built environments are often referenced as primitive or vernacular. Sometimes spontaneous or popular environments are often referred to as traditional. While these settlements are different from traditional built environments, they are the closest thing to them these days (Rapoport, 1989).

3.2.3 Change and the resilience of traditions Within the built environment, traditions involve the settlementâ&#x20AC;&#x2122;s spatial patterns and organization, social structure, territorial control and ownership. All these aspects that are defined by tradition are subject to change. Properties of behavioral norms are all reflected in the patterns of public and private spaces within the settlement (Tuan, 1989).

Traditional built form responded effectively to change in culture (Rapoport 1990). As a result, traditional systems are now being regarded as resilient management alternatives (Adger, Kelly, & Ninh, 2001). This resilience is thought to be supported through col-

36 lective inner spirit (Crysler, 2003). Individual differences in traditional environments are much less compared to contemporary ones. The increasing rate of individuality that comes with the process of modernization results in a rupture in the continuity of tradition (Rapoport, 1989). One can still observe effective communication in traditional setting and spontaneous (squatter) settlements more than in professionally designed environments (Rapoport, 1990). Batty and Longley in their study on fractal cities, states that when systems are changed, they change at a local level rather than globally (Batty & Longely, 1994). In this way they develop a degree of spatial resilience that is manifested in the persistence of their form as can be seen in many of the traditional city cores around the world (Batty & Longely, 1994). He also mentions that the uniqueness and autonomy of the traditional dwellings and settlements is an outcome of the internal resilience of tradition itself. This is evident in the capacity of traditional buildings and modes of social organization to cope

with challenges like rapid urbanization (Batty & Longely, 1994).

Tuan associates tradition with constraint, where constraint means a return to un-

questionable customs and moral codes (Tuan, 1989). In traditional built environments,

techniques of construction and the use of space are being formalized in accordance with customs, and with known and tried techniques. As a result, traditions and norms of behavior turn into a coordinated system and codified framework of behavior (Bourdier, 1989).

There is a distinction between traditions and customs: while a characteristic of traditions is invariance, custom does not preclude innovation and change; it cannot afford to be invariant (Hobsbawm & Ranger, 1983; Oliver, 1989). Tradition is interpreted here as a rule system while custom is the manner in which it is practiced (Oliver, 1989).

3.2.4 Šarīʿah and fiqh Regarding the notion of rules, Otto defines Islamic law (Šarīʿah ‫ )شريعة‬as a set of rules based on the revelation by God to the Prophet Mohammad (Otto, 2010). Islamic jurisprudence (fiqh ‫ )فقه‬was developed to interpret Šarīʿah from the available resources (Qur’an and Prophet's sayings). It has been the principle objective of Islamic scholars to discover and develop the Šarīʿah as a concrete body of rules and principles (Otto, 2010). Fiqh has been able to cope with the diversity in Muslim societies as a result of its open,

37 discursive nature, which bridges the gap between divine abstract source and variety of human behaviors and contexts.

Fiqh ‫ فقه‬is the interpretations of Islamic jurists (fuqaha’ ‫ )فقهاء‬of the code of conduct (Šarīʿah) expounded in the Qur’an, often supplemented by the Prophet’s deeds and sayings (Sunnah ‫سنَّه‬ ُ ). Fuqaha’ used several tools such as analogy (qiyas ‫ )قياس‬and historical consensus (Ijmāʿ ‫ )إجماع‬to arrive at a set of principles (fiqh) that interpret the rules of Šarīʿah. This process is known as (ijtihad ‫)اجتهاد‬. This resulted in the emergence of several schools of thoughts with different views on the details of applying Šarīʿah (madh’hab ‫)مذهب‬. Fiqh can be regarded as the process of gaining knowledge of Islam through jurisprudence (Levy, 1957). Fiqh refers to the body of Islamic law extracted from detailed Islamic sources, which are studied in the principles of Islamic jurisprudence (usul alfiqh ‫( )أصول الفقه‬Levy, 1957). Fiqh covers two main areas: rules in relation to actions (‘amaliyya ‫ )عملية‬and Rules in relation to circumstances surrounding actions (wadia’ ‫)وضعية‬. There are also two main

‫))معامالت‬9002 ،‫ (التويجري‬.

groups of Fiqh: Worships (Ibadaat ‫ )عبادات‬and Dealings and transactions (Mua’malaat

Šarīʿah can be regarded as constant or as a tradition. Traditions constitute the general structure that is resilient to change over time (Hobsbawm & Ranger, 1983). Fiqh is dynamic, for it is about how the general principles of Šarīʿah are applied in the various and ever changing aspects of life. It can be considered as a robust mechanism to deal with change in relations and needs )9002 ،‫(زرواق‬.

Due to the limited scope of the study at hand, it only focuses on the traditional built environments in the Middle East region that were mostly inhabited by Arabs and ruled, during a certain period of time, by the Islamic Šarīʿah, hence they are mostly referred to in the study at hand as the Arab-Islamic built environments. It is worth noting that the same aspect of resilience can be valid for socio-cultural rules system in traditional contexts of other regions, such as the Mediterranean and African regions (Hakim, 1986; Hakim, 2001; Hakim, 2008).

3.2.5 Change, tradition and continuity: the case of the ArabIslamic city Neither Qur’an nor Sunnah (Prophet’s deeds and sayings) contains explicit urban planning codes that could be implemented in planning and designing Muslim built environments. On the other hand, Islam, through its Šarīʿah, has provided principles that organize the way of life in Muslim communities and their built environments (Mortada, 2003).

Šarīʿah, as Islamic legal tradition can be considered as a shape of tradition (AlHathloul, 1981). However, since tradition implies imitation, it should be made clear how it was able to adapt to change (Al-Hathloul, 1981). In the traditional Arab-Islamic city, the process of growth and change was regulated by a framework of legal principles (qawaíd fiqhiyya ‫)قواعد فقهية‬. Within this framework, a system of commonly understood rules was followed and respected in decision making (Hakim, 2010). Table 3.1 shows the ﬁve principles that served as the basis upon which secondary principles and rules were established.

Principle

la Ḍarar wa-la Ḍirar‫ال ضرر و ال ضرار‬

The rest of this chapter will refer only to the first and last principles. Description

Do not harm others and others should not harm you

al-umur bi-maqasidiha ‫األمور بمقاصدها‬

Affairs are determined by their intent

al-yaqin la yazul bi-l-shakk ‫اليقين ال يزول بالشك‬

Certainty is not removed by doubt

al-mashaqqa tajlib al-taysir‫المشقة تجلب التيسير‬

Hardship brings relief

al-ada muhakkima ‫العادة م َح َّكمة‬

Custom has the weight of law

Table 3.1 The five main legal principles of fiqh (qawaíd fiqhiyya ‫)قواعد فقهية‬, Based on (Hakim, 2010)

These principles represented a set of overarching rules that guided the behavior of individuals within the built environment and the interactions among them (Hakim, 2010). Consequently, these principles had a significant influence on the built form of cities in the regions under Islamic rule. These set of rules were mainly characterized by their implicit and proscriptive nature. This allowed for the generation of a diversity of innovative solutions in response to the surrounding condition (Hakim, 2007).

Traditional Muslim cities are characterized by their complex urban fabric, which is the product of an accumulative process of activities over time. In shaping their built envi-

39 ronment, people were subconsciously influenced by the rules of conduct that originated from the Šarīʿah, and were guided by Fiqh. These rules that turned into legal mechanisms were documented by Muslim scholars for jurisprudence purposes, a few of which were recently discovered through the study of old manuscripts that were mostly published in Arabic, Persian and Ottoman languages. Any analysis of the urban form and morphology of Muslim cities must pass through the understanding of these social codes of conduct that acted as an informal regulation system and formed an underlying system in Muslim societies (Ben Hamouche, 2009b).

3.3 Traditional Rules System “The rule system is defined as the underlying system of rules and codes, which Islamic culture has established to guide and control societal activities, including decisions and activities related to design and construction.”

(Hakim, 2001, p. 87)

Hakim mentions two types of rules system; one is a centralized imposed set of rules

that was previously discussed and referred to as (qawaíd fiqhiyya ‫)قواعد فقهية‬. Hakim refers to

these principles as “meta-principles”. The other is a system of localized community-based customary rules (‘Urf ‫)العرف‬. These two types of systems operated simultaneously in Islamic culture (Hakim, 2001).

Building activity was the concern of Islamic fiqh from its very early phases as it is concerned with all aspects of public and private life of Muslims. Problems arising from building activities were viewed by fiqh as problem arising from interaction2 amongst people (Hakim, 1982). Applying the principles of fiqh in the context of the built environment provided the freedom to act within certain limits. Thus fiqh was proscriptive in nature in the sense that it is not prescribing specific preconceived requirements for solving problems (Akbar, 1988a). This liberty allowed generating responsive solutions for local problems

The notion of interaction among agents will be discussed in chapter 4 as a quality of Complex Systems.

40 within local conditions. Thus diversity is achieved, since every locality becomes unique in character (Hakim, 2008). The system incorporates customs as well as adapting to changes in these customs across time.

Table 3.2 lists some of the main societal processes that are closely related to the built environment, mostly based on the work of Hakim (2008) and Akbar (1988a). These processes had their direct impact on the form of the traditional Arab-Islamic city. A rules system that is based on fiqh principles was applied to these societal processes and regulated the design and construction activities and decisions related to them accordingly3.

Principle

Description

‘Urf ‫العرف‬

Customs

Tawr ̄ith ‫التوريث‬

Inheritance

Shuf‘ah ‫الشفعة‬

Pre-emption

Ihy ̄a ‫إحياء األرض الموات‬

Land revivification

Ḍarar ‫الضرر‬

Asbaqiya ‫حق األسبقية‬

Irtifaq ‫حق االرتفاق‬

Fina’ ‫فناء‬

Principle of damage Right of precedence

No.

Servitude Right of appropriation of open spaces

Table 3.2 Societal rules system based on fiqh, based on the work of Hakim (2008) and Akbar (1988a)

In the following some of the above mentioned societal processes are further explained and their impact on the built form of the Arab-Islamic city is demonstrated and discussed.

Translations and transliteration used are according to (Al-Hathloul 1981)

3.3.1 Customs ‘Urf ‫العرف‬ Some scholars refer to the verse 7: 1994 in the Qur’an as the basis for sanctioning ‘urf. The term refers to all that is customary to a people and which they follow in their say-

ings, acts and in what they reject (Hakim, 1994). This has been operationalized through a set of fiqh principles mentioned by (Hakim, 2001) such as: 

People’s customs must be respected and followed ‫المعروف عرفا ا كالمشروط شرطا ا‬



Time might change those customs and new solutions will be needed ‫األعراف‬ ‫قابلة للتغير عبر الزمن‬

As shown in the above principle, ‘urf is dynamic as it changes with time. It can be initiated in a top-down manner by a local authority or at least encouraged. Another way is that experiences evolving from responding to local conditions of the surrounding environment can be handed from generation to another in a bottom-up process.

Acknowledging ‘urf made it possible to cope with the diversity on the micro level

while maintaining unity on the macro level. Hakim (1994) provides a possible explanation of this observation. Unity was mainly due to the application of consistent Šarīʿah princi-

ples all over the Islamic nations, while diversity was achieved by the recognition of the lo-

cal customs (‘urf) by the Islamic law. This interface between the broad concepts of Šarīʿah and local attitudes rooted in various Islamic societies (‘urf) demonstrates the flexible nature of the rules system based on Islamic fiqh. It shows that it is a system of law that is performance-based and proscriptive in nature (Hakim, 1994).

Within traditional Arab built environments, Islamic law was operational on a daily basis in the realm of houses and markets (Akbar, 1984). The smaller the scale the more evident the impact of ‘urf was on the built environment, for it is closely related to the domain of individual decisions and interactions. It is more evident, for example, in housing clusters (Ben Hamouche, 2009b).

“Take things at their face value, and bid to what is customary [or accepted by local tradition, and turn away from the ignorant” English translation based on (Hakim, 2008, p. 144). 922 ‫"خذ العفو وأمر بالعرف وأعرض عن الجاهلين" سورة األعراف‬ 4

3.3.2 Inheritance Tawr ̄ith ‫التوريث‬ It is the subdivision of a property that belongs to a person who has died into portions according to prescribed shares of inheritors as prescribed in Islamic law and conditions of use such as accessibility, lighting, and so on (Hakim, 2008). Inheritance laws were responsible for increasing the size of the owing part and resulted in unifying responsibility in small groups (Akbar, 1988a).

One of the consequences of this inheritance mechanism was the fragmentation of the assets into smaller, interlocked but functional parts. New components such as corridors, staircases, doors for access and windows often emerged within the existing built fabric to make the existing components functional (Fig. 3.1). Laws of inheritance largely influenced the mechanisms of subdivision in the traditional Islamic cities, thereby increasing the com-

plexity of the urban fabric and the fractal dimension5 of the city (Ben Hamouche, 2009b).

Figure (3.1) The impact of Inheritance on hypothetical urban fabric. Source: (Ben Hamouche, 2009b)

Fractal dimension is a measure of the irregularity or complexity of a system. Knowledge of fractal dimension helps to pinpoint the key variables in the dynamics of a system (Goldstein 2001).

3.3.3 Pre-emption Shuf‘ah ‫الشفعة‬ This is where the priority is given to a co-owner or close neighbor to get the share of the other partner in a property (Akbar, 1988a). This principle had an opposite effect to the inheritance law as it reunified smaller fragments into one larger property as shown in Figure 3.2 (Ben Hamouche, 2009b). Over time, this principle increased the share of the owing party with the largest share and over time led to unified responsibility of a single

individual (Akbar, 1988a).

Figure (3.2) The impact of pre-emption on hypothetical urban fabric. Source: (Ben Hamouche, 2009b)

The previous two principles are among five mechanisms that affected the size of the property in the traditional Arab-Islamic city that were discussed by Akbar (Akbar, 1988a): sadaqah charity ‫صدقة‬, hiba endowment ‫هبة‬, inheritance, pre-emption and selling. They were chosen for their contrasting impact on the built environment and relevance to the study at hand. Through time these mechanisms led to complex relationships among members of the owing parties.

3.3.4 Land revivification Ihy ̄a ‫إحياء األرض الموات‬ This principle was extracted from the Prophet Mohammad (PBUH) saying, "The people are God's people, the land is God's land, he who revives a piece of dead land will

own it, and the unjust root has no right”6 (Akbar, 1988a, p. 28).

Figure (3.3) Impact of revivification on hypothetical urban fabric of the traditional city. Source: (Ben Hamouche, 2009b)

Land is considered ‘dead’ if there is no trace of building or cultivation; if it is not used by the neighboring locality as, for example, a burial ground, or as a source of wood or food for cattle. Streets were greatly influenced by the principle of revivification (Akbar, 1984). Leftover spaces, as well as over-head spaces along paths and streets, were subjected to continuous appropriations by residents. Encroachments on streets, cantilevers, projections such as mushrabiyyat, and rooms over-arching streets are physical manifestations of this principle in the built environment (Ben Hamouche, 2009a).

(Akbar, 1988a, p. 28)

‫ وليس لعرق ظالم حق‬،‫ فمن أحيا من موات األرض شيئا فهو له‬،‫ والبالد بالد هللا‬،‫العباد عباد هللا‬6

45 Land revivification implied an accretion of decisions where each previous decision or action represented a constraint for future interventions (Akbar, 1988a). One consequence of this principle for public space was the gradual disappearance of leftover spaces that could not be maintained by the authorities (Fig. 3.3). As a consequence of the extension of the responsibility of the residents for their outdoor spaces, most urban spaces were marked by signs that denoted a sense of territoriality for individuals as well as groups. This ensured protection from outsiders and increased social interaction among residents (Ben Hamouche, 2009a).

3.3.5 Principle of damage Ḍarar ‫الضرر‬ According to the Prophet’s saying (PBUH), "there should be neither harming nor reciprocating harm”7 (Akbar, 1988a, p. 26). This is one of five principles discussed earlier in this chapter, which jurisprudence is based upon. Hakim mentions one of the fiqh principles that were reached by jurists in order to apply the Prophet’s saying in the built envi-

greater ones.8

ronment (Hakim, 2001): It is sometimes necessary to tolerate lesser damages so as to avoid

The principle of damage implies moral control as well as the control of decisions affecting the built environment. It draws the broad limits of the freedom of action as long as others are not harmed (Akbar, 1984). A large margin of freedom of action was enjoyed by the society and individuals in shaping their properties and environment. Freedom of action was legalized through another secondary fiqh principle (Hakim, 2001): The basis for action is the freedom to act9. This freedom was evident in the dynamic process of building and continuous transformations that took place at the time these principles prevailed (Ben Hamouche 2009a).

(Akbar, 1988a, p. 26) ‫ الضرروالضرار‬7 (Hakim, 2001) ‫ الضرر األشد يزال بالضرر األخف‬8 (Hakim, 2001) ‫ األصل في األشياء اإلباحة‬9

3.3.6 Right of precedence Asbaqiya ‫حق األسبقية‬ Applying principle of damage led consequently to what can be called ‘right of precedence’. This is where the rights of the pre-existing buildings on a site should prevail over buildings that are built later (Akbar, 1984). This rule were supported and legalized through a fiqh principle that states that older established facts must be taken into account by adjusting to their presence and conditions10 (Hakim, 2001). Relationships between properties were organized through this principle, with respect to the rights of original or earlier usage.

The right of precedence may not result in an organized built environment in the common sense, but it will generate autonomous environment where all decisions were in the hand of the largest size residing party (Akbar, 1984). Each party realized its responsibility and rights in the physical environment. Agreements were the basis of the right of precedence (Akbar, 1984). This right establishes a chronological priority in the environ-

ment. It makes it obligatory for actors to consider the pre-existing conditions before acting and to come up with innovative solutions to overcome the surrounding constraints. Thus,

tions (Ben Hamouche, 2009a).

the building process becomes a chain of specific solutions that exclusively fit their loca-

3.3.7 Servitude Irtifaq ‫حق االرتفاق‬

Servitude is among two categories of properties discussed by Akbar (1988a): servitude (Irtifaq ‫ )االرتفاق‬and leasing (Intifa’ ‫)االنتفاع‬. In the context of compact built form with very little public space, the right of servitude was established. Servitude occurs when a property is owned and controlled by one party and used by another (Akbar, 1988a). This is a principle that induces residents to facilitate to each other, by way of charity and benevolence, the mutual use of their properties (Ben Hamouche, 2009a). For example residents may have the right to discharge their rain water through their neighbor’s roof or inhabitants may have access to their property through their neighbor’s house.

(Hakim, 2001) ‫ القديم يترك على قِدَمِ ه‬10

47 Within these overlapping domains, subdivision, incremental growth and conventional transactions were three mechanisms that resulted in what is known as easement right. Easement right is the exclusive benefit of a property over another adjacent one in which the two properties are owned by different parties. The study of this right improves our understanding of the traditional built environment from a territorial point of view (Akbar, 1988a).

At the physical level, agreements and easements generally led to a network of relationships and uses, and any further building action was therefore undertaken within a more complicated set of site conditions (Ben Hamouche, 2009a). This principle implies an overlapping area of responsibilty (Akbar, 1988a). Servitude right was not hindered under any circumstances regardless of any changes in the external property (Akbar, 1988a). However, servitude cannot be established without the owners’ agreement.

3.3.8 Right of appropriation of open spaces (Fina’ ‫)فناء‬ Fina' refers to the interior courtyard of a house or the outdoor space on the street

abutting to one's property. Residents of this property exclusively owe the right to use it or

to give the permission for other to use it (Akbar, 1988a; Hakim, 2008). Fina' can be used for sitting, parking, and mobile vendors11. This rule was set by the Caliph Omar Ibn Alkhattab, as mentioned by Ibn al-Rami12 in his book documenting building codes in the 14th century Islamic west (Hakim, 2008).

3.4 Responsibility and Control In the following the impact of the rules system on the Arab-Islamic built environment will be demonstrated through the notions of responsibility and control.

This situation still exists in the contemporary built environments in the Middle East region. The main difference is that the control of these spaces belongs to central authorities instead of the residing party (Akbar, 1988a). 12 Hakim refers to Ibn al-Rami as a master builder who wrote a complete treatise on building construction. He used a lot of the material from those earlier Arabic manuscripts in addition to his own experiences and interpretations from being a master builder (Hakim, 2008).

48 Responsibility is a theme that is linked to the notion of change and control. It determines the structure of the built environment (Akbar, 1988a). The theory of responsibility is how Akbar tries to understand the ontology of the physical environments and its creators.

The qualities of the built environment can be improved by changing the patterns of responsibility (Akbar, 1988a). According to Akbar, patterns of responsibility are the main difference between the structure of the traditional and contemporary built environments. The percentage of owing parties who control is much higher in the traditional built environment than in contemporary centralized cities, where large population nor own neither control. The shift in responsibility, or as Moudon (Moudon, 1986) refers to it as ‘loss of control’, impact goes beyond the immediate residential scale13 to affect neighborhood and city form. Parties with no control over their built environments are considered by Akbar as

irresponsible and dissipate resources of the society (Akbar, 1988a).

The control of a property or using it is different from its ownership (Akbar, 1988a).

According to Akbar, control is the right to manipulate elements without necessarily using

or owing them. It is important to note that the term ‘property’ is usually associated with ‘ownership’ as much as the term ‘territory’ which is related to ‘control’ (Akbar, 1988a). The size of the controlling party affects the condition of the property (Akbar, 1988a). Decisions that would affect the built environment, such as closing a street or building a second floor, are decided upon by the controlling party. Akbar suggests that to identify the controlling party can be achieved by tracing the change in the built environment across scales (Akbar, 1988a).

The notion of responsibility is closely related to the Islamic legal system (Šarīʿah). According to Akbar, Šarīʿah invests the claim of control in the owner (Akbar, 1988a). In traditional cities, buildings and urban spaces were transformed by the hands of people

This is clearly evident in control of fina’ or outdoor spaces abutting to properties (Hakim, 2008).

49 whether users or owners with very little or often in the absence of governmental or professional authority. In this sense, the built environment is regarded as a process rather than product. The potential of the built environment depends on the degree of responsibility enjoyed by the direct user (Akbar, 1988a).

Change in the organization of the built environment influence the zones of responsibility. The principles of the traditional rules system discussed earlier considered relationships between parties as a series of constraints. These principles produced ordered built environment in which responsibility is clear (Akbar, 1988a). This shows that it is the very internal logic of the organization of the Muslim city and its capacity to evolve with certain robustness in the face of time’s perturbations that have produced the most resilient, successful, and noteworthy urban systems, all over the wide region where Islam prevailed (Raymond, 2008).

3.5 Conclusion This chapter introduces to the notion of tradition and the traditional: its meaning, at-

tributes and association with the built environment. This notion was discussed to the no-

tions of change and resilience. An introduction and distinction between the general definitions of Šarīʿah and fiqh. It was shown that Šarīʿah is a constant framework and fiqh is transformation mechanism that enables it to adapt to different conditions across time.

The relation between Šarīʿah and fiqh on one hand and the built environment of the Arab-Islamic city can be studied through want is known as the traditional rules system. This has been achieved throughout this chapter by defining a few of the main principles of this system and showing their impact on the built environments. It has been shown how a few set of principles generated complex urban fabrics and how these principles influenced this built environment’s ability to deal with change over time.

The chapter demonstrated the impact that this traditional rules system had on the Arab-Islamic built environment through the discussion of two important aspects: responsibility and control in relation to Šarīʿah. In the next chapter the notion of resilience will be traced through what is known as Complex adaptive systems (CAS).

CHAPTER FOUR

RESILIENCE IN COMPLEX SYSTEMS

“Cities should be identified, understood, and treated neither like simple mechanical systems nor like disorganized complex systems, but as organized complexity.”

(Jacobs, 1961, p. 434)

4.1 Introduction This chapter discusses the resilience of complex systems. It defines complex adaptive systems and discusses its characteristics. The chapter introduces the Complexity Theory of Cities (CTC) and uses it as a base to explain the complexity of the traditional built environment.

4.2 Complexity and Resilience The following section will discuss how the notion of complexity is related to the concept of resilience.

4.2.1 Complexity

Figure (4.1) Complexity as the domain between Order and Chaos. Source: (Appelo, 2009)

Complexity can be regarded as an intricate order that is resilient to random shocks (Chu, 2011). Complexity paradigm changes our focus from the top-down to the bottom-up view with emphasis on structure and global order emerging from multiple simple local actions (Batty, 2007b). The notion of random interactions on the local level often makes complexity associated with disorder and chaos. This makes complexity considered to be the domain between linearly deterministic order and indeterminate chaos that can be called ‘deterministic chaos’ (Byrne, 2008) as Figure 4.1 shows. The development of deterministic Chaos Theory is computer-dependent. Starting from a deterministic situation the theory shows how, by means of an iterative process, the system moves from order to chaos (Portugali, 2011).

Theories concerned with ‘order out of chaos’ emerged in the 1960’s including complexity and self-organization theories. Chaos Theory and Fractal Theory have since become one of the leading theories of complexity. The terms ‘chaos’ and ‘fractals’ are sometimes used simultaneously or interchangeably. For instance, the fractal dimension can

52 be viewed as a relative measure of complexity, and thus of chaos (Ben Hamouche, 2009b), while fractals are presented as part of Chaos Theory (Gleick, 1987). Fractal Theory can be also regarded as a subset of Chaos Theory as it is a geometric manifestation of complexity (Haghani, 2011). Chaos and Fractal Theories rely on a series of concepts that establish their structure and define their methodologies and techniques. Among the concepts that are directly linked to the physical environment are growth and self-similarity, randomness and unpredictability, dynamism and nonlinearity, order and disorder (Ben Hamouche, 2009b).

Before we proceed, an important distinction between the terms ‘complicated’ and ‘complex’ is in order. In a complicated system, the various components maintain a degree of independence from one another. Thus the absence of one component may reduce the degree of complication but does not necessarily affect the system’s behavior. The complexity of a system results from the dependency of components on each other (Miller, 2007). Thus, unlike complication, complexity is an embedded property of a system unlike complication. Complicated systems are reducible but complex systems are not (Miller, 2007).

This is why complexity is often adopted by anti-reductionist approaches to science, as it

provides a holistic view that does not overlook the notions of interaction and organization.

4.2.2 Self-organization

Cilliers tells us about two ‘indispensable’ capabilities of complexity or complex systems: representation and self-organization (Cilliers, 1998). This study is concerned with the later. As much as complex systems are fragile, they can be extremely robust to changes in their surrounding environments due to their emergent behavior. This emergence is a result of the capacity of self-organization (Miller, 2007).

Self-organization, as a concept, was originally introduced to contemporary science in 1947 by the psychiatrist and engineer W. Ross Ashby and immediately adopted by cybernetics scientists. In the 1960’s it became associated with general system theory. It did not become common in the scientific literature until it was adopted by physists and researches in the field of complex systems in the 1970’s and 80’s. Cilliers proposes a definition of self-organization as “a property of complex systems which enables them to develop or change internal structure spontaneously and adoptively in order to cope with, or manipulate, their environment” (Cilliers, 1998, p. 80).

53 The process of self-organization in complex systems works as follows: the information that flow into the system influences the interaction of the system components. As the system encounters different conditions in the surrounding environment, it generates new structures to deal with these conditions, within the experience built in the system from its history (Cilliers, 1998). An example of self-organizing systems is language. “The laws of language do not tell us what to say, but prescribe the structure and the limits of the sayable” as Bill Hillier is quoted in an interview by Philip Ball (Ball, 2004). Although language has a recognizable structure, this structure needs to be adjustable in order to maintain its function in different circumstances. Furthermore, since language is used by individuals, these adjustments may take place by individual decisions. Therefore, global changes in the language structure results from the large number of interactions on individual basis (local level) (Cilliers, 1998).

The example above demonstrates how self-organization works on different levels and within different constraints. But despite these differences among complex systems, the

process of self-organization has a number of general characteristics (Cilliers, 1998):  A result of the interaction between the system and its environments;

 Involves nonlinear process;

 Dynamically adapt to changes in the surrounding environment;  Emergent property of complex systems;  Always has a history (learn from experience);  Complex.

The complexity of self-organized systems is of two folds; one, is that they are constituent of numerous components where there is no technical way to establish causal relations among them; two, is that these components are interconnected in a nonlinear fashion by a complex network of feedback loops. Mathematically, this form of behavior can be described by a set of nonlinear equations (Portugali, 2011).

Self-organizing systems respond to change using two mechanisms: fluctuations and chance. Fluctuation is the ability to destabilize the system depending on their scale (Allen, 1996). This can be evident in the discussion of how the issue of scale has a significant impact on responsibility in built environments as discussed previously in section 2.3.2. The

54 smaller the spatial extent of the fluctuation, the more difficult it will be for it to spread into the environment (Allen, 1996). For this reason self-organizing systems are sometimes referred to as far-from-equilibrium or at the edge of chaos systems. An example of this was discussed earlier in section 3.3.1 on the influence of ‘urf on the diversity in the built environment that becomes more evident the smaller the scale.

The second mechanism, chance, concerns the behavior of the system near instability1 (Allen, 1996). It is through successive instabilities, which are spatial in some cases, complex behavior emerges in the system, as actors interact with each other in both competitive and co-operative ways. Each actor, taken separately, may have very simple decision criteria and desires, but the dynamic folding of the system can give rise to complex patterns and flows (Allen, 1996). Even if the actors’ spatial distribution is governed by a deterministic set of rules, the notion of chance appears quite naturally because of the many possible spatial structures that can emerge through bifurcations2 of choices in decision trees3 (Allen, 1996). At this point it may be useful to note Rapoport’s emphasis, discussed in chapter

ments.

two, on how maximizing users’ choice is critical in enhancing the resilience of environ-

The capacity to adapt and respond to external and internal variations may require some ‘instability’. This can be the origin of the system’s resilience (Allen, 1996). Therefore, self-organization leads to the view that both the structure and the fluctuations in it are the result of the evolutionary process, and that the adaptability and resilience that result are natural properties of complex systems (Allen, 1996).

Instability is the condition of a system when it is easily disturbed by internal or external forces. It is a characteristic of what can be known as far-from-equilibrium systems (Goldstein, 2001). 2 Bifurcation is when a system exhibits an abrupt deviation from typical behavior. A change in organizational policies that results in long-term change of an institution can be considered an example of bifurcation (Goldstein, 2001). 3 A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes (Goldstein, 2001).

4.3 Complexity in the Built Environment This section will demonstrate how built environments can be regarded as complex systems. It traces this back to social sciences concerned with the city then it shows how the complexity theory of cities developed. In the end of the section a focus is made on the complexity in the Arab-Islamic traditional built environment.

4.3.1 Complexity in social systems Social sciences have been concerned with the ‘spatial’ since 1970’s (Byrne, 2008). From the social science view, cities are considered as organizational social systems that their structure is changed through various decisions made through time based on diversity of choices (Batty, 2007b). Decisions result from mutual interactions on the local level through a web of connections between multitudes of social agents that social systems are composed of. The complexity of interactions makes it difficult to predict change and results in a nonlinear behavior. This basic feature is responsible for the production of com-

plexity in social systems (Miller, 2007).

4.3.2 Evolution of Complexity paradigm of cities

The science of city planning responded to the problems of the city through two main paradigms. During the first half of the 20th century the city was viewed as a machine. Controlling the city through deterministic and top-down plans was the modernist planners’ solution for the poor living conditions of the industrial cities of the 19th century. In the second half of the 20th century the city was regarded as a system. The science of complexity can be the basis for the third paradigm shift in city planning (Haghani, 2011).

The city as a system The rise of Dynamic Systems Theory in the 1960’s motivated city planners to revise traditional urban planning as popularized in various texts (Batty, 2007b). This systemic approach replaced the rigid planning methods with more flexible planning policies. The city was considered as a system, where numerous subsystems interact to create the whole. Accordingly, the city planning process included defining a systematic and hierarchical relation(s) among structural elements, by which any change in any element of the city is to correspond to the construction of the whole system. A system that would easily accommodate

56 all the activities of a large number of people while having the flexibility to absorb growth and change. Thus, designing a city shifted from predicting the future of the city to predicting a structure of the city (Haghani, 2011).

One of the limitations of this approach is that it considered cities as systems in equilibrium and the planning role is to maintain this state. Although it is more realistic than the mechanistic approach, it was still considered by a group of city theoreticians and planners to be deterministic in nature (Haghani, 2011). For this group, this approach, still being top-down in nature, limited user participation which clearly conflicted with aspects of democratic city life (Batty, 2007b). Eventually, this has led to the rise of Complexity Theory as a paradigm in city design.

The city as a complex system â&#x20AC;&#x153;Cities should be identified, understood, and treated neither like simple

(Jacobs, 1961, p. 434)

plexity.â&#x20AC;?

mechanical systems nor like disorganized complex systems, but as organized com-

Jacobs was one of the first theorists who called for treating the city as an organized complexity, the subject of life sciences, rather than as a machine (Haghani, 2011). The two previous approaches did not deal with the notion of uncertainty and complexity in the city. Organized complexity proved to be a constructive way of thinking about urban systems revealing their capacities using the tools of feedback, neighbor interaction and pattern recognition that are the hallmark of emergence in all self-organizing systems, as discussed earlier in this chapter (Johnson, 2001). Jane Jacobs argued that we should trust the selforganizing vitality of cities rather than received ideas of what they should look like (Ball, 2004).

Since the 1980â&#x20AC;&#x2122;s there has been a growing trend to consider the city as a complex system suggesting a radical shift from top-down, centralized management to more decentralized bottom-up growing systems that evolve and change as a result of the accretion of decisions (Akbar, 1988b) and choices, actions and interactions of millions of agents, that generates complex structures that cannot be controlled or managed from the top-down

57 (Batty, 2007a). After more than 25 years of Jacobs (1961) intuitive, cities are no longer regarded as disordered systems. Beneath the apparent chaos and diversity of the physical form lies a hidden order or pattern language as Christopher Alexander calls it (Alexander, 1979). This global order emerges from the multiple decisions taken on and individual level and various processes of interactions.

Tension between chaos and order in Complexity Theory is intuitively appropriate for the study of organic cities such as the case of Arab-Islamic cities. These cities are of a dual character. They are seen as chaotic as they are mainly characterized by their irregular geometry. However, when one considers the fact that they emerged, and still re-emerge, governed by a deep underlying structure, they can be considered as symbols of order. It is only recently, from the view of Complexity Theory, that irregularity in geometry is considered as a sign of richness rather than as simply a lack of order (Haghani, 2011).

Chaos Theory and the science of complexity, provide efficient instruments for uncovering this underlying structure. Irregularity should be regarded as the result of a set of

rules that governed the successive physical events that gave shape to the city, which re-

curred in layers over time. Therefore, the factor of time that is the age of the city defines the degree of urban complexity and is evident in its morphology through the intensity of events (Ben Hamouche, 2009b).

Complexity Theories of Cities (CTC) The various complexity/self-organization theories and approaches have been suggested since the emergence of this paradigm in the 1960â&#x20AC;&#x2122;s. Most theories of complexity that have been applied to cities can be considered as a whole domain of theory and research that is called Complexity Theories of Cities (CTC) (Portugali, 2011). The domain of CTC already includes a rich body of research on fractal cities (Batty & Longely, 1994), selforganization and the city (Portugali, 2000), cities and complexity (Batty, 2007a), cellular automata and agent-based urban simulation models (Benenson & Torrens, 2004), studies on cities as networks, and much more (Portugali, 2011).

According to Portugali (2011), two major types of CTC can be identified as longterm (or comprehensive) versus short-term complexity theories. Long-term (comprehen-

58 sive) complexity theories are long-term and ‘comprehensive’ in the sense that they refer to all stages of the evolution of such systems; the bottom-up process of emergence that brings complex systems into a global ordered state and the process of steady state that keeps them is a structurally stable state. Short-term complexity theories concentrate on the process of ‘emergence’, that is, the bottom-up process by which local interaction between the parts gives rise to a global structure (Portugali, 2000).

CTC has achieved two main aims. First, they provided a single intact theoretical basis to a various urban phenomena that were once perceived independent from each other. Second, it suggested a new insight into how cities are understood in reference to properties such as nonlinearity and emergences, as well as the notion of chaos vs. order that do not necessarily contradict one another (Portugali, 2000).

4.3.3 Complexity and the traditional Islamic city

In Islamic cities the process of incremental growth and development that emerged from small local actions was organized through a set of endogenous rules and behavioral

norms. These set of rules stemmed from the symbiosis between Islamic jurisprudence and

the specific conditions in each region and city. This interface resulted in establishing a set of unwritten implicit codes that structured this generative process of growth (Hakim, 1994; Hakim, 2007). Ben Hamouche refers to these codes as factors of complexity in the traditional Muslim city. Thus studying those underlying principles helps decompose the complex patterns of the traditional urban fabric in old Muslim cities (Ben Hamouche, 2009b).

4.4 Complex Adaptive Systems (CAS) The notion of complexity is often associated with the notion of system. Complex systems approach allows the exploration of the system’s degree of robustness as the system autonomously reacts to all kind of changes (Miller, 2007).

Cities are claimed to be complex systems for the chaotic behavior they show and their emerging fractal geometric patterns. In order to examine the credibility of this claim that a city can be observed as a self-organizing complex system, we need to go through the characteristics of Complexity Theory (Haghani, 2011).

59 CAS are a special case of complex systems. In addition to their complexity as they are made up of diverse interconnected elements, they also have the ability to adapt to change and learn from previous experiences. They are open, nonlinear, self-organizing systems that have the ability to adapt to changing conditions through changing the rules that organize the random autonomous interactions between agents and the environment. This adaptation takes place through gradual gained experience that is reflected in the agentâ&#x20AC;&#x2122;s behavior. Interacting agents that are described in terms of certain rules generate complex temporal patterns (Holland, 1995). Thus unanticipated, emergent structures play a critical role in the evolution of these systems (Goldstein, 2001). In order to understand how CAS work, these patterns need to be studied. Table 4.1 lists the main characteristics of complex systems sorted into four categories.

Information

Identity Scale

Complex Adaptive Systems

Self-organization Emergence Nonlinearity Flows

Rules

Complex systems Deterministic Chaos Self-organization Emergence Limited predictability Adaptability Feedback Interconnectedness Sensitivity to initial condition Variety Irreducibility Hierarchy and levels of scale Self-similarity

Category

Diversity Aggregation

Table 4.1 Characteristics of Complex systems and CAS according to (Haghani, 2011) and (Holland, 1995).

4.4.1 CAS and rules Complex systems exhibit what can be called deterministic chaos (duality of determinism and randomness). This is when random behaviors are generated without violating the overall rules of the whole system. These rules determine the systemâ&#x20AC;&#x2122;s general character, behavior, the way agents interact (Haghani, 2011). The behavior of agents in nonlinear

60 complex system exhibits both deterministic and random natures. Haghani uses a term that is based on Jon Cooper’s work4, to describe this dual nature as "complexity through rules". Out of these local rules complicated and unexpected patterns emerge. Emergence within complex systems occurs with no pre-design in a bottom-up manner (Waldrop, 1992). In other words, macroscopic behavior emerges from microscopic interactions (Cilliers, 1998). Emergence is when a higher level pattern arises out of parallel complex interaction between local agents.

Steven Johnson mentions four core principles of emergence: neighbor interaction, pattern recognition, feedback, indirect control (Johnson, 2001). Therefore emergent systems are rule-governed systems. Their capacity for learning and growth and experimentation derives from their adherence to local-level rules (Johnson, 2001). Understanding emergence has always been about giving up control letting systems govern themselves as much as possible and letting a system learn from experience (Johnson, 2001). Hillier supports this argument, as he sees that good urban planning involves relinquishing some con-

trol (Ball, 2004).

Due to the quality of emergence in complex systems, there is always limited predictability and uncertainty about the outcomes of the process of change that originates from the bottom-up (Batty, 2007b). Nonlinear interactions between complex system components almost make the behavior of these aggregates more complicated to be forecasted by summing or averaging. Therefore complex systems are irreducibility; they cannot be reconstructed by simply adding its elements together. This is known in the general systems theory as ‘wholeness’ (Haghani, 2011).

Self-organization is the process when the new emergent structures, patterns arise in a complex system without external imposition and with no prior design. It is a dispersed

Jon Cooper PhD thesis is entitled ‘The Potential of Chaos and Fractal Analysis in Urban design’ and his current research interest focuses on the development of fractal based townscape evaluation techniques (Oxford Brooks University, 2013). 4

61 feature across a system, for it is not controlled centrally through a command-control manner. This means that a complex system is not predetermined by the property of an individual component, but is the result of patterns of interactions between elements and themselves and the surrounding environment (Goldstein, 2001; Haghani, 2011). Self-organizing complex systems possess the ability to adapt to new situations and changing conditions within and around their environments. This adaptation capability is the result of evolutionary processes (Haghani, 2011). According to the Darwinian evolutionary theory, adaptation is the progressive process of a living organism to become ‘fit’ to a continuously changing environment. Adaptation by adjusting the rules of interaction among the agents of a system is fundamental characteristic of complex systems. The adjustment of these rules comes from the accumulation of experiences (Goldstein, 2001).

4.4.2 CAS and information When information flow to a system or a subsystem from outside its boundaries this

process is called ‘feedback’. The feedback process can explain the sequential change in a system where the behavior of the element influences the way other elements act through a

series of relationships (Haghani, 2011). As mentioned previously in section 2.2.1, in the

characteristics of resilient systems, there are two kind of feedback: positive and negative.

An example of flows can be the flow of goods or capital into cities. Holland (1995) suggests that the coherence of the city is imposed on a flux of people and structures. Flow can be over a network of nodes and connectors (a kind of graph), were nodes are agents and connectors are possible interactions. Flows vary through time (Holland, 1995).

Complex systems exhibit great sensitivity to their initial conditions. Their nonlinear nature amplifies slight changes in the initial conditions. Infinitely small changes in the starting condition of a complex nonlinear system will result in dramatically different output of the system. This feature makes their behavior difficult to be forecasted (Goldstein, 2001; Haghani, 2011). Hence complex systems are characterized by the highly interconnectedness of its components at a local level and to its environment at a global level (Haghani, 2011).

4.4.3 CAS and identity Complex systems consist of a variety of interacting agents or subsystems. As the number of these agents increases, their behavior becomes more unpredictable. An example for this can be the economic system of a city where people dynamically interact by lending, borrowing, investing and exchanging money and goods (Haghani, 2011).

Holland argues that the diversity that exists in CAS is neither accidental nor random (Holland, 1995). He explains that it is a quality that arises from the potential interactions between agents. Diversity in CAS is a dynamic pattern; a pattern of interactions that is when get disturbed at any moment of time, has the ability to re-organize itself. This ability is what makes diversity a main characteristic of resilient systems. Diversity in CAS is the result of progressive adaptations. Each new adaptation opens the possibility for new

4.4.4 CAS and Scale

interactions.

Complex system self-organize through creating ordered hierarchy on interconnec-

tions across different levels of scale (Haghani, 2011); where self-similarity is the symmetry

across scales. It implies recursion (Gleick, 1987). Elements that form these self-similar patterns are interconnected in a nonlinear fashion (Haghani, 2011). In CAS, Holland calls this â&#x20AC;&#x2DC;aggregationâ&#x20AC;&#x2122;; this quality concerns the emergence of complex large scale behaviors from aggregate interactions of less complex agents on smaller scale (Holland, 1995).

4.5 Computational Models of Complex Systems As Complexity Theory is concerned with structures that come into being selforganized through their emergent properties, it can be defined as the study of everchanging complex systems based on computational concepts of recursion (Haghani, 2011). Tools and ideas emerging from the study of complex systems research can complement existing scientific approaches and allow researchers to build better theories about the world. Hollandâ&#x20AC;&#x2122;s attempt to model emergent behavior of CAS (Holland, 1995) made it often associated with certain types of computer simulation.

63 First, a distinction should be made clear between complexity theories and complexity models. Theories are concerned with the dynamics and properties of complex systems, while models are a means to study the various phenomena and properties that characterize complex systems (Miller, 2007). Miller sees that theories should be separated from the tools used to derive them. He further explains that tools are only to be seen in the light of how much they can enhance scientific research. On the other hand, theories are judged on how they improve our understanding of the world (Miller, 2007).

One of the most powerful tools arising from the research in complex systems research is a set of computational models such as CA (cellular automata), AB (agent-based) and graph-theory models. Inspired by the concepts of generative systems, these models are becoming central in simulating complexity. In generative systems, order and patterns are built from the bottom up using a few basic rules that occurs in space through time (Batty, 2007a). Depending on these rules, the patterns can be extremely varied and unpredictable. This kind of models emphasizes bottom-up emergence processes of complex systems.

These models very closely resemble the dynamics of the complex systems of the cities.

The use of these models allows for a much wider range of systems to be explored (Miller, 2007). Miller draws our attention that tools often get mistaken for theories. For example

these computational techniques and their mathematical derivations can be wrongly assumed to be the real scientific statement (Miller, 2007).

Models are often confused with simulation. However, according to Miller, modeling focuses on simple entities and interactions while simulation is a kind of complicated structure of models (Miller, 2007) (Fig. 4.2).

John Miller argues in his research on CAS that computational models can be more than a simulator for theorized phenomena they might as well be a productive theoretical

Figure (4.2) Modeling vs. simulation. Source: (Miller, 2007)

64 generator (Miller, 2007). Computational tools can be very useful for building theories of complex adaptive social systems, as they provide a wider potential for explorations of how these systems begin and grow. Computational models allow us to study more complex environments with greater precision (Miller, 2007). An important remark made by Miller is that the use of computer is neither necessary nor sufficient for a model to be considered as computational (Miller, 2007). Implementing computational concepts such as recursion and bifurcation is what gives the model its computational nature.

The study at hand is concerned with computation as a tracer of nonlinear complex emergent processes. A core principle in computation is that global complex patterns emerge from local simple rules (Coates & Thum, 1995). Generative modeling using computers can be a means to carry out endless experiments to explore key ideas in the design of built environments.

Several experiments have been conducted to interpret CAS and their emergent spatial properties such as multi-agent systems, cellular automata and recently, genetic algo-

rithms5 that adopt a bottom-up philosophy (Geipel, Kr채mer, & Kunze, 2005). These exper-

iments fall under the computational paradigm in which computational models are used to describe social systems and natural phenomena (Hoekstra, Kroc, & Sloot, 2010).

4.5.1 Computational social science Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions (Macy & Willer, 2002).

Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems. This is done by being open to random events and chance. GA utilizes techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossoverInvalid source specified..

65 In the discipline of sociology, social complexity is a conceptual framework useful in the analysis of society. Contemporary definitions of complexity in the sciences are found in relation to systems theory, where a phenomenon under study has many parts and many possible arrangements of the relationships between those parts. At the same time, what is complex and what is simple is relative and may change with time (Waldrop, 1992).

4.5.2 Modeling complexity in the built environment Complexity Theory represents a paradigm shift in the use of computational models which have been traditionally used in quantitative urban morphology research. Computation can be a useful tool in exploring the influence of some very simple rules on the transformation of the city (Coates & Thum, 1995). Computational models such as cellular automata (CA), agent-based (AB) and graph-theory models are becoming among the most dominant approaches in the study of cities as complex, self-organizing systems (Portugali,

2011).

The attractiveness of CA and AB models to the study of cities as self-organizing

complex systems stems from their computational potential due to the use of differential

equations in these models (Portugali, 2011). CA models are built of discrete spatial units that are the cells similar to cities that are built of discrete spatial units such as houses, lots, and city blocks. In real cities the properties of local spatial units, such as land value, are determined, to a large extent, in relation to their immediate neighbors; the properties of the cells in CA models are determined in a similar manner. These resemblances make CA models, intuitively and mathematically, natural tools to simulate urban processes (Portugali, 2011).

A cellular automata (CA) model is a two or three dimensional lattice of cells, where each individual cell can be in one of several possible states (e.g. empty, occupied, etc.) and has one out of several possible properties (e.g. developed, underdeveloped, poor, rich, etc.). The dynamics of the model is generated by an iterative process. In every iteration, the state of each cell is determined by some transformation rule(s). The rules are local in the sense that they refer to the relations between the cell and its nearest neighbors. Local interrelations and interactions between cells entail global structures, behaviors and properties of the system as a whole (Portugali, 2011).

66 However, the dynamics of cities is dominated not only by local relations between its infrastructural physical elements but also by local and global relations between the many active agents in the city such as human individuals, families, households, firms and public agencies. This is where agent-based simulation models come in; their aim is to mimic the behavior and action of the many urban agents (Portugali, 2011).

Agent-based (AB) models focus on agents, in place of, or in addition to, the cells of CA: Each agent is seen as a decision maker that behaves and interacts with other agents and the surrounding environment according to a set of predetermined rules (similar in nature to the transformation rules of CA). These rules might include also feedback rules that affect the further behavior and action of the agents. This nature of these rules allows agents to â&#x20AC;&#x2DC;learnâ&#x20AC;&#x2122;, adjust their behavior and thus adapt to changing conditions (in real life these can be social, cultural and/or environmental). Agents thus have global relations that are determined by local rules (Portugali, 2011). These kind of computational models allow objects to directly interact with one another on a local level. Accordingly, they can be considered

as bottom-up models. Most significantly these kind of models overcome reductionism in

traditional ways of modeling (Miller, 2007).

Free agents on a cellular space (FACS) are a family of simulation models specifically designed to deal with urban dynamics in general and with social and cultural urban segregation in particular. The central idea of FACS is that to holistically consider three sets of relationships in order to be able to capture the essence of urban dynamics: the interrelationships between infrastructural urban elements such as buildings, parks, roads, etc.; the interrelationships between the various urban agents, and, the interrelationships between urban agents and urban physical elements. FACS models are built as a superposition between two layers corresponding to two kinds of models: AB and CA (Portugali, 2011).

Following in this section a few examples are mentioned. They illustrate the potential of the previously mentioned computational tools/models on the study of built environments.

Islamic city algorithm Islamic city algorithm is a computational model that simulates the spatial structures of Mediterranean cities such as Damascus that has developed over centuries will be discussed. In the simulation the observer needs to be a well-defined part of the system; as a local agent (Coates, 2010). This model tries to tackle the issue of how a set of simple rules can be responsible for generating complexity through the means of feedback loops within

the process.

Figure (4.3) A computational model to simulate spatial structures of Mediterranean cities. Source: (Coates & Thum, 1995)

In this kind of agglomerative simulations, outcomes should be distinct from the initial condition otherwise the results can be claimed to be already contained in the instructions to produce these results (Coates, 2010). For example the cul-de-sac in the following model is not directly built into the rules set for the model (Fig.4.3). This remark being noted, it is valid to assume that this algorithm capture some essential process of how this spatial structure emerged rather than just mimicking the look of it (Coates, 2010). The algorithm is based on a set of assumptions: ď&#x201A;ˇ These urban systems have developed through slow agglomerations based on individual decisions. ď&#x201A;ˇ At any time all buildings need to be accessible to each other and the main street. ď&#x201A;ˇ There is a sort of communal global structure for access (main street)

68 During the recursive runs of the code, a set of cells (labeled either as ‘empty space’ or ‘houses’) propagate randomly over a plane with certain areas marked as ‘streets’. Thus it depends on a gradual filling up process constrained by the following rules:  You can build anywhere as long as you do not block out any existing building’s access to the rest of the city.  At least one side of each house is accessible from the road. Usually these dead-end streets are occupied commercially by a similar trade or/and extended family. The model shows that cul-de-sac is an emergent spatial structure based on social organization (Coates 2010).

Hakim (1982) studies a similar pattern in the same Damascene context. He mentions a similar rule that was applied on dead-end streets in the traditional city; that is every res-

ident can build anywhere as long as it does not block out any existing building's access to

the rest of the city. The process that the algo-

rithm discussed earlier, grow in a similar manner to the one by Akbar (1988a). First, there is a sprinkle of isolated houses then a recursive network emerges the accretion of decisions depending on the existing pathways (Fig. 4.4).

City of slums ‘City of Slums’ is another example of

Figure (4.4) Emergent recursive networks. Source: (Akbar, 1988a)

modeling complexity in the built environment. This project combines the ideas generated by two simulating exercises: one is called the Favela Project (Sobreira, 2007) and the other is Peripherisation Project (Barros & Sobreira, 2002). These experiments aimed to model the spatial growth process of squatter settlements in Latin American cities.

Figure (4.5) Settling patterns (a) Sequence of favela outputs, with attractive boundaries at the bottom and right side only; (b) development process of Ashaiman settlement in Acera. Source: (Barros & Sobreira, 2002)

The favela project simulates the spatial development of spontaneous settlements on a local scale. These settlements develop in a self-organized manner starting from attractive boundaries such as existing streets that bound the site (Fig. 4.5). In the experiment, randomly free agents over a cellular space (FACS) are constrained by these boundaries. Hence the spatial development is simulated or constrained according to rules that are based on

boundaries.

Figure (4.6) Variations of consolidation parameters. Darkest areas are the most consolidated. Source: (Barros & Sobreira, 2002)

In this model agentâ&#x20AC;&#x2122;s rules are much like actual settlers who search for attractive urban site to settle. There is a feedback procedure involved, where the agents change their decisions according to density. This process is much like real life where the settlement starts with scattered building and as the density increases more agents take longer time to search for an empty plot and open spaces between buildings get occupied (Barros & Sobreira, 2002).

Figure (4.7) Process A&B show experience with different initial conditions through across time (t). Source: (Barros & Sobreira, 2002)

Peripherisation model simulates the process of urban growth through the expansion

of the city borders in the form peripheral settlements. In the model, the population consists of three economic groups which are assumed to share the same preference to settle close to

the area best served with infrastructure, nearby commerce and job opportunities. What is

(Barros & Sobreira, 2002).

different among these groups is their ability to relocate based on their economic power

The ‘City of Slums’ model builds on the ‘Peripherisation’ model while adding a consolidation rule (Fig.4.6). This rule refers to the process of consolidating of spontaneous settlements along time into favelas that are harder to evict. In this model time is measured through a number of iterations. This opens up the possibility to test different initial conditions (Fig. 4.7) and explore different emergent system behavior (Barros & Sobreira, 2002).

4.6 Conclusion This chapter introduced the concept of Complexity Theory and how it developed to be closely related to systems theory. The relation between self-organization, as a significant characteristic of complex system, and the notion of resilience were drawn in the course of discussing the main characteristics of complex systems. A closer look was given

71 to a specific type of complex systems that is Complex Adaptive Systems and its characteristics.

It has been shown how computation is a valuable tool in modeling and understanding of complex adaptive social systems. Several kind of computational models such as Cellular automata and agent-based models were discussed throughout this chapter.

The notion of complexity were discussed in relation to the built environment. It has been demonstrated how social systems including cities can be considered as complex systems. The evolution of the complexity paradigm of cities starting from how the city was regarded as a system then specifically as a complex one and how this has led to the development of a domain called Complexity theories of cities. How computational models were used to interpret the dynamics of city growth was demonstrated through two simulation precedents: Islamic city algorithm and city of slums. The chapter ends with a brief remark

on the notion of complexity in the traditional built environment. In the following chapter

tional Rules Graph (CRG).

interrelation between the three discussed systems So far will be drawn using the Computa-

CHAPTER FIVE

THE COMPUTATIONAL RULES GRAPH (CRG)

“By linking many concepts, drawing attention to mechanisms and so on, this approach provides a conceptual framework for the topic and promises to lead to the development of theory”

(Rapoport, 1989, p. 97)

5.1 Introduction In this chapter an attempt is made to establish a relationship between the systems discussed in the preceding chapters. The relations are mapped in the form of a graph that will be referred to as Computational Rules Graph (CRG). These relations are verified and supported using three interrelated bodies of literature (Complexity Theory, Resilient Systems and environment behavior studies).

cultural rules and the resilience of the space across time through many decades and across scale form the room to the neighborhood. The works of N.J. Habraken (2000) and J. Turner

(1977) were amongst the most significant studies to tackle the issue of socio-cultural rules,

using the exact terminology, in housing and relate to the issue of responsibility and control. This area of research relates just two bodies of literature: environment and behavior studies and Resilience Theory.

The computational aspect the work of Hillier and Hanson and their team (Hillier & Hanson, 1984) and (Hanson, Hillier, Rosenberg, & Graham, 1998) is considered the base for dealing with the social aspect based on the work of Kent (1993) and other anthropology and ethnographic research of the built environment. Hillier’s work (Space Syntax) is mainly analytical, descriptive. Using the results of these analytical methods, some generative work has been done such as the research conducted by Adam Doulgerakis (2007) incorporating genetic programming tools. Another significant research is the work of Carl Bovil (1996) on fractals at the architectural scale, especially the vernacular and traditional environments and the work of Michael Batty (Batty & Longely, 1994) at the city scale. These aforementioned studies in a way or another have related Complexity Theory to the environment and behavior studies. This relation has been further studied theoretically in the works of M. Ben Hamouche (2009a; 2009b), and applied in the work of Paul Coates

74 (Coates & Thum, 1995) that was demonstrated in section 4.4.3 under the title ‘Islamic City Algorithm’.

This study will try to establish a number of interrelations between different fields of literature (Resilient Systems, Complexity Theory and environment behavior studies) to identify patterns that may reveal a theoretical framework. As illustrated in Figure 1.5, the built environment in this chapter will be studied from three different perspectives based on the following systems: 1. Resilient systems 2. Traditional rules system 3. Complex systems

In the previous three chapters, an attempt was made to relate the three systems mentioned above to the built environment. In this chapter, further interrelations between 

these systems will be explored: Based on chapters two and three, a number of relations that are shared be-

tween the principles of the traditional rule system and attributes of resilient 

systems are highlighted.

Based on chapters two and four, a number of relations are drawn between the attributes of resilient systems and complex systems.



Based on chapters three and four, a number of relations are established between principles of the traditional rules system and the attributes of complex systems.

By establishing this framework, the study aims to show that the resilience of the traditional socio-cultural rules systems that regulate and organized the building activities in the traditional built environment was a factor in the resilience of these environments. This resilience is claimed to be due to the self-organization capacity and emergent nature that this rules system generates. This will be illustrated using a graph that maps the relations between the attributes of these fields. This graph will be dubbed as Computational Rules Graph (CRG) (Fig. 5.11).

5.2 The Computational Rules Graph (CRG) In the following a number of subgraphs will be reviewed. These subgraphs are superimposed to form the Computational Rules Graph (CRG) which will be revealed toward the end of this chapter. These subgraphs can be regarded as an elaboration on the relations presented in the graph/diagram shown in Figure 1.5. When overlaid, these subgraphs are supposed to show that the socio-cultural rules system based on Islamic jurisprudence (fiqh) had a self-organizing impact on activities in the traditional built environment (Hakim, 2008) hence this rules system was a major factor in the resilience of these built environments.

The CRG (a superimposition of the following subgraphs) will demonstrate, through the verification of the wired connections mapped in the CRG, that since the principles of traditional rules systems and the attributes of resilient systems share a lot of connections with the attributes of complex systems, therefore traditional rules system are resilient in

nature and are a factor of complexity and resilience in the built environment.

In Figure 5.1 attributes of each system are represented as cluster of nodes. Each

cluster represented is based on a different body of literature. These nodes are wired together to form a set of subgraphs. Each single wire in each subgraph shows a specific concept in one cluster (that represents a body of literature) in relation to a concept in another cluster. Each bundle of wires that are shown in the subgraphs or the CRG corresponds and represents one of the relations illustrated in Figure 1.5. Each subgraph is based on an anchor node that may belong to any of the four clusters, and then the wires unfold connecting other nodes, whether from the same cluster or another, in a non-sequential order.

Relations represented in each subgraph are verified and supported by examples that relate attributes of the built environment to the attributes of each system. The objective here is to demonstrate the approach rather than reach solid conclusions. It is important to keep in mind while reviewing the sub-graphs that they do not necessarily form a closed loop. This mainly because of the complex nature of the attributes represented in the graph as some subgraphs is connected to others. The graph was separated into these subgraphs demonstrated in this chapter for the sake of making it easier to follow the relations.

Figure (5.1) Cluster of nodes containing the attributes of systems discussed in the previous chapters

Figure (5.2) Red subgraph with â&#x20AC;&#x2DC;urf as its anchor node. The graph demonstrates the impact of â&#x20AC;&#x2DC;urf on the diversity in the built environment.

5.2.1 Red Subgraph The following graph (Fig. 5.2) has ‘urf ‫ عرف‬as its anchor node in the traditional rules system cluster. ‘Urf was discussed in section 3.3.1 as a significant part of the traditional rules system. ‘Urf’ node is related to the quality of ‘diversity’ in the complex adaptive systems, which in turn is related to ‘adaptation’ quality of complex systems. Both qualities of adaptation and diversity are related to the ‘dynamic interaction’ featured in the built environment cluster. In addition to the dynamic interaction, ‘interface pattern’ node is also connected to the ‘urf’ node in the traditional rules system cluster. ‘Urf is also related to the quality of ‘diversity’ in resilient systems.

Complex systems consist of a ‘variety’ of subsystems or a large number of interacting elements. Holland argues that this ‘diversity’ exhibited in CAS is neither accidental nor random. According to him, diversity in CAS is a pattern of ‘dynamic interactions’ between agents (Holland, 1995). This pattern, when disturbed at any moment of time, has the ability

to self-organize (Holland, 1995). A diverse structure can enhance the adaptability of a system, increasing it resilience (Haghani, 2011). This explains why diversity is an attribute of

resilient systems as previously discussed in section 2.2 ‘adaptation’ in CAS is of a progres-

sive nature as each new adaptation opens the possibility for new interactions (Holland, 1995).

As briefly noted in section 4.4.4, the traditional built environment can be regarded as a complex adaptive system that included a variety of interactions among agents on a local level. The acknowledgement of ‘urf ‫عرف‬, as discussed in 3.3.1, was the main source of this diversity in the traditional built environment. This interface between the broad unified nature of Šarīʿah and the diversity of local customs across regions, demonstrates the resilient nature of the rules system.

This graph showed that ‘urf, which is an integral component of the traditional rules system, is a common factor between the complexity of the built environment evident in its diversity thus it is a source of its resilience.

Figure (5.3) Blue subgraph with inheritance and pre-emption as anchor nodes. The graph shows the impact of these attributes in increasing the complexity of the built environment

5.2.2 Blue Subgraph The subgraph in Figure 5.3 relates the quality of ‘self-similarity’ in the complex systems to the ‘change in property size’ in the built environment using the principles of inheritance and pre-emption in the traditional built environments as its anchor nodes. These two nodes are in turn related to the complexity of resilient systems. In the built environment cluster, the ‘unpredictable spatial patterns’ node, that result from ‘unpredictable decisions and actions’ of the stakeholders, is linked to the qualities of ‘emergence’ and ‘limited predictability’ of the complex systems. The traditional rules system and the complex systems clusters meet each other in the nodes of the slow knowledge and redundancy in the resilient systems cluster.

In the case of the city, global order and ‘unpredictable spatial patterns’ emerge from the bottom-up random unpredictable actions on the local level (Haghani, 2011). Unpredictable spatial patterns emerged within the traditional city in multiple ways. One can be due to

emption’ or ‘inheritance’.

‘change in property size’, whether due to ‘pre-

Pre-emption, where the priority is given to a co-owner or closet neighbor to get the share of the other partner in a property (Akbar, 1988a), lead to the aggregation of property in the built environment. Aggregation is a characteristic of CAS discussed in section 4.3. This process increased the generated complexity in the urban fabric (Ben Hamouche, 2009b). For example, spatial elements such as crossover passages appeared to connect two properties across the street into one, without obscuring the circulation route

Figure (5.4) Crossover passages. Source: (Hakim, 1994)

(Fig. 5.4).

The complexity that is generated by unpredictability is considered to be a principle attribute of resilient systems. It gives the built environment the capacity to exist in alternate stable state, as previously discussed in section 2.2.

81 The principle of inheritance when applied to the built environment, led to the subdivision of property (Fig. 5.5), as opposed to the impact of preemption. These recursive subdivisions increased the complexity of the urban fabric and the fractal dimension of the city (Fig. 5.6). This can be evident in the bifurcation of streets (Fig. 5.7) and the self-similarity of courtyards across Figure (5.5) The recursive process of subdivision/aggregation of property in the traditional urban fabric of Hammet city, Tunisia. Source: (Ben Hamouche, 2009a)

the traditional Muslim cities (Ben

Hamouche, 2009b).

Figure (5.6) Fractal simulation of the self-similarity in the streets of Cairo Source: (Eglash, 1999)

Figure (5.7) The impact of inheritance or land subdivision in Algiers Source: (Ben Hamouche, 2009b)

The Qaâ&#x20AC;&#x2122;a prototype is another example of self-similarity in the Arabs-Islamic cities. The same pattern existed across scales with different variations (Fig. 5.8). This selfsimilarity was always maintained over centuries as a result of cultural norms and local, verbally transmitted know-how (Akbar, 1988a) or what is discussed earlier in section 3.1.1 as â&#x20AC;&#x2DC;urf. This aggregation of experiences preserves the interconnectedness of components among the system.

Figure (5.8) Self-similarity of qaâ&#x20AC;&#x2122;a traditional dwelling prototype in traditional al-Medina, Saudi Arabia Source: (Akbar, 1988a)

Complex systems consist of elements that form self-similar patterns interconnected in a nonlinear fashion (Haghani, 2011). Self-similarity means symmetry across scales and it implies recursion (Gleick, 1987). On a different level, self-similarity can be related and lead to the redundancy that is a main characteristic of resilient systems discussed in section 2.2. Therefore the notion of self-similarity can help increasing the resilience of the built environment as a whole.

The subgraph aimed to show how the influence of the inheritance and pre-emption principles of the traditional rules system, on the change of the property size in the built environment increased its complexity as evident in the notions of limited predictability and self-similarity. This complexity generated by the slow knowledge can thus be considered as a major factor of the resilience of the traditional built environment.

Figure (5.9) Orange subgraph with â&#x20AC;&#x2DC;right of precedenceâ&#x20AC;&#x2122; as an anchor node. The graph shows the impact of this principle on the incremental change in the built environment.

5.2.3 Orange Subgraph The subgraph in Figure 5.9 relates both the ‘emergence’ and ‘sensitivity to the initial conditions’ properties of the complex systems to the feature of ‘incremental change’ in the built environment and the notions of ‘autonomy’, ‘responsibility’ and ‘dynamic interactions’ in the traditional built environment through the ‘right of precedence’ which belongs to the traditional rules system which in turn is connected to the ‘slow knowledge’ node in the resilient systems cluster.

Emergence is when a higher level pattern arises out of parallel complex dynamic interaction between local agents (Johnson, 2001). As previously mentioned in section 4.2, among the core principles of emergence are neighbors’ interaction, feedback and indirect control that implies autonomy. Autonomy of the stakeholders was a significant attribute of the traditional built environment that emerged from the application of fiqh rules system. Since emergent systems are rule-governed, their capacity for learning and growth and ex-

perimentation derives from their adherence to low-level local rules (Johnson, 2001). Understanding emergence has always been about giving up control, letting systems autono-

mously govern themselves as much as possible, and learn from slow knowledge (Johnson,

2001). Slow knowledge is a principle attribute of resilient systems, as previously discussed in section 2.2. This aggregation of experiences preserves the interconnectedness of components among the system.

The principle of right of precedence that was applied in the traditional city were preceding actions may continue while every new action was questionable. This rule resulted in autonomous environment where control was in the hand of the largest size residing party and each party recognized its responsibility in this environment (Akbar, 1984). Right of precedence can be related to a characteristic of complex systems that is called sensitivity to initial condition, where infinitely small nonlinear changes in the starting condition of a system will result in dramatically different complex output of this system (Haghani, 2011). Within the city, a series of cause-effect process of incremental change often start with small-scale actions that have an emergent potential (Ben Hamouche, 2009a; Hamdi, 2004). In the case of the traditional built environment this is also called 'accretion of decisions” (Akbar, 1988b). This accretion can be regarded as slow knowledge that enhances the resilience of the built environment, as previously discussed in section 2.2.

Figure (5.10) Black subgraph with the principle of damage as an anchor node. This graph shows how this principle with the amount of freedom of action it allowed generated complex built environment within a set of rules (complexity through rules).

86 Through establishing the relations discussed above, this subgraph aimed to show that the right of precedence was a factor in the resilience of the built environment. Incremental change based on slow knowledge emerged from the application of this principle of the traditional rules system.

5.2.4 Black Subgraph The following subgraph (Fig. 5.10) relates the ‘principle of damage’, represented as a node in the traditional rules system cluster, to the qualities of ‘irreducibility’, ‘limited predictability’ and ‘deterministic chaos’ of the complex systems. These qualities are evident in the ‘unpredictable decisions and actions’ in the built environment. This all relates to the ‘complexity’ as a characteristic of resilient systems.

Jane Jacobs (1961) argued that the city is a living organism with complex interlinkages and holistic behavior. Components of a complex system are closely interconnect-

ed together at a local level and to its environment at a global level (Haghani, 2011). This makes complex system irreducible, meaning that it cannot be reconstructed by simply add-

ing its elements together. These two notions are behind the complexity of socio-ecological

systems which greatly enhances its resilience, as previously discussed in section 2.2.

Another feature of a complex system is the notion of limited predictability about the outcomes of process of change that originate from these bottom-up processes (Haghani, 2011). The main source of this unpredictability in the city is the unpredictable decisions and actions of users as free agents. Random behaviors in the city were generated within a set of few simple rules that govern the whole system. This condition can also be known as ‘complexity through rules’ (Haghani, 2011). These rules that determine the system’s general character and behavior, the way agents interact. The source of these rules in the case of the modern city can be the planning policies and building regulations.

Figure (5.11) Green subgraph with â&#x20AC;&#x2DC;land revivificationâ&#x20AC;&#x2122; as anchor node. The graph aim to show that this principle enhanced the social networks and regulated the responsibility patters within the built environment.

88 In the traditional built environment interactions between stakeholders were organized according to the ‘principle of damage’ among other rules. This principle allowed for the freedom of actions based on multiple unpredictable individual decisions. Yet these random actions were controlled by a simple rule of not causing any harm to others. This resulted in a condition that is referred to by Haghani (2011) as ‘deterministic chaos’ where behaviors of agents in a complex system are randomly generated yet they are determined by the rules of the system.

As we can see from the above, applying these kind of simple rules significantly contributed to the complexity of the traditional Arab-Islamic built environment and thus increasing its adaptability and resilience.

5.2.5 Green Subgraph In the subgraph shown in Figure 5.11 the principle of ‘land revivification’, which

belongs to the traditional rules system, is related to feedback, which is a characteristic of complex systems. Feedback is closely related to the notion of ‘flow in the CAS cluster.

Feedback in the built environments is evident in the ‘unpredictable spatial’ and ‘interface

patterns’ in general and the ‘dynamic interactions’ in the traditional built environment in specific. The subgraph shows how these relations are connected to the resilient systems through the nodes of ‘social networks’ and ‘tight feedbacks’.

Complex systems structure and organization emerges without pre-design. It is the result of patterns of interactions between agents themselves and their surrounding environment. This happens through the recursive process of feedback that requires a flow of energy and information. The information is stored in forms or patterns within the system, conveying a kind of memory (Holland, 1995). Feedback can be one of the reasons behind the incremental change in a system where the behaviors of elements influence the way other elements act through a series of relationships. As previously discussed in section 2.2, resilience of a system is significantly enhanced through feedback loops among various components of a system that effectively transmit slow knowledge.

Figure (5.12) The Computational Rules Graph (CRG), a superimposition of the previously discussed sub-graphs (Fig. 5.2-5.11).

90 Through their interpretation of interface patterns, human users are the main source of feedback in the city (Haghani, 2011). In the case of traditional Muslim built environment, one of the main principles in the rules system that greatly enhanced the process of feedback was the principle of land revivification (Akbar, 1988a). The act of ‘land revivification’ resulted in gradual transition of responsibility of leftover space in the urban fabric from authorities to residents hence the amount of social interaction among the controlling parties increased significantly (Ben Hamouche, 2009a). This incremental process of ‘land revivification’ generated unpredictable spatial patterns, increasing the complexity of the traditional Arab-Islamic built environment. Thus, as previously discussed in section 2.2, maintaining tight feedback loops through strong social networks was critical in supporting the resilience of this complex system.

This subgraph aimed to demonstrate that the right to revivify land in the traditional rules system motivated the process of feedback throughout the built environment via the notion of responsibility among stakeholders. Due to this feedback process the social net-

5.3 Conclusion

works were greatly intensified producing a more resilient built environment.

In this chapter, three different bodies of literature (resilience systems, Complexity Theory and environment and behavior studies) were interrelated to show that the application of the traditional rules system (based on Islamic fiqh) enhanced the resilience of the traditional built environment through the capacities of emergence and self-organization.

These interrelationships were presented in a graph dubbed the Computational Rules Graph (CRG) (Fig.5.12). This graph consists of four clusters of nodes where each cluster represents a system based on the aforementioned bodies of literature. Each cluster contains a number of nodes that represent the main characteristics of this system. By connecting (wiring) these nodes together a number of subgraphs emerge. An attempt was made to verify the relations represented in each subgraph with the support of the main bodies of literature previously mentioned and examples from the built environment

91 It is worth noting that the subgraphs shown in Figure 5.12 still need further verification. Due to the limited scope of the study, this graph can be further expanded by studying other interrelations where more subgraphs can be extracted. Also the connections between the subgraphs themselves may further be studied. A thorough network of relations and attributes of the built environment can be reached by tracing all possible connections (for further explorations refer to the enclosed transparencies).

As the presented graph links many concepts from different areas of research, it can help in generating and developing a theory. The CRG can provide a framework to map previous experiments conducted on the built environment using computation. It can also be a base flow chart for future algorithms designed for innovative applications in planning of

the built environments.

CHAPTER SIX

CONCLUSION

"Traditional design is a treasure house of human experience, of successes and failures and of ways in which built environments interacted with ecological settings and culture."

(Rapoport, 1989, p. 100)

6.1 Summary This study aimed to show that the resilient nature of the traditional rules system based on Islamic law played a major role in increasing the complexity of the traditional built environment and its self-organizational capacity, hence its resilience and capacity to deal with change over long periods of time. This objective was sought through the analysis, interpretation and interrelation of three different bodies of literature (Resilience Theory, environment and behavior studies and Complexity Theory).

In the first chapter, the study began by introducing the main three concepts that it is based upon: resilience, socio-cultural rule, and complexity. In the three chapters that followed, the notion of resilience was traced in three different systems: resilient systems, traditional rules system and complex systems (Fig. 1.4). Each chapter began with some basic introductory ideas related to the system to be discussed. This was followed by listing the main attributes and characteristics of the system. In the end of each chapter, the relation

between the system of interest and the built environment was discussed.

In chapter five, an attempt was made to map the interrelation between these three

systems and the built environment. This was done using a graph that was called the Computational Rules Graph (CRG). This graph acted as a theoretical framework to show that since the principles of the rules system based on Islamic law that governed and shaped the traditional built environment are closely related to the attributes of complex system and since complexity is an inherit attribute of resilient systems therefore, traditional built environments are resilient due to the complexity created by the application of the rules system.

Following is an elaboration on how simple rules as those presented in the traditional rule system can generate the kind of complexity manifested in the traditional Muslim built environments and how this contributed to the resilience of these environments.

6.2 Discussion As previously noted, cities are considered as organizational social systems that their structures change over time. Organizational systems can be of two types: hierarchical and

94 spontaneous. The organizational structure of these systems is determined by the ‘span of control’ (Zywick, 1998).

In hierarchical systems the actions and decision-making process is centrally directed from the top. In contrast, in spontaneous orders actions arise from millions of mutual transactions on the bottom level between individuals. Thus, decentralization can be regarded as a defining characteristic of spontaneous orders, where most of decision-making authority belongs to the base (Zywick, 1998). An example for this in the traditional built environment was demonstrated through the application of the right of precedence where control of property was dispersed to the residing party. It was noted in section 2.2 that overlay hierarchical systems limits the capacity to adapt to change. Thus, complex systems will be more effectively governed by decentralization spontaneous principles which make these systems more resilient. In practice, this can imply relinquishing more control to actors on

the local levels.

As more control is in the hand of individuals, rules need to be easier to understand

and implement in the decision making. An example of simple rules applied in the tradition-

al built environment is the principle of damage.

“Complex rules for a complex world are an invitation to a disaster.” (Epstein, 1995, p. 140)

Epstein1 argues that complex systems demand simple rules rather than complex ones. Epstein believed that traditional laws are more attuned to the modern world with all its complexities (Epstein, 1995). Highly decentralized complex systems, suggested above, necessitates the simplicity of the governing rules (Zywick, 1998).

Richard Allen Epstein is a distinguished American professor of law and considered as one of the most influential legal thinkers of modern times. Epstein is an advocate of minimal legal regulationInvalid source specified..

95 Epstein’s legal simple rules were mainly concerned with two aspects that are closely related to the built environment: personal autonomy and property acquisition. Personal autonomy is an attribute of free society, where each individual agent is held responsible for his/her well-being (Barry, 1998). The influence of applying the principles of the traditional rules system, such as the right of precedence, on the issue of responsibility in the traditional built environment were discussed in section 3.3. Epstein is aware the most sociallyefficient rule about ownership is the first possession (Barry, 1998). Similarly, this aspect was the concern of the traditional rules system based on fiqh such as in the case of the principle of land revivification.

The interaction of agents through social networks2 produces an aggregate entity that is more flexible and adaptive than its components. Aggregation3 of units in large clusters enables them to set their own objectives thus being autonomous (Johnson, 2001). The built form of the traditional Arab-Islamic city can be considered as an emergent4 result of slow accumulation of knowledge, decisions and actions governed by rules system. The ad-

vantage of this accretion of decisions that it was based on real situations and involved real autonomous users within real site constrains. This creates a system is so interrelated, which

is a feature of complex systems5. This accretion of knowledge and experience is a key to an

efficient adaptable built environment (Akbar, 1988b).

“Traditional cultures have displayed unexpected Resilience.” (Ibrahim, 2002, p. 238)

The uniqueness and ‘autonomy’6 of the traditional dwellings and settlements is an outcome of the internal resilience of tradition itself (Crysler, 2003). This is evident within the traditional built environment in the application of principles such as right of precedence

‘Social networks’ is a feature of resilient systems discussed in section 2.2.1. and located in the CRG in section 5.2.5 3 Aggregation characteristic of CAS discussed in section 4.3.1 and located in the CRG in section 5.2.2. 4 Emergence is a characteristic of complex systems and is represented in section 5.2.3 5 Autonomy is discussed in section 4.2 and illustrated in section 5.2.5 6 Incremental change is part of the subgraph discussed in section 5.2.3. 2

96 and land revivification as discussed in more detail in chapter 3. This internal resilience is evident in the resilient capacity of traditional buildings and modes of social organization to cope with challenges like rapid urbanization and globalization.

Traditional practices contain the Genotypes7 which can produce more resilient contemporary urban living patterns. Traditional communities are knowledgeable and capable of self-organization that shows livelihood resilience based on intangible values, which in the context of Arab-Islamic communities are deeply rooted in Islamic religion.

Traditional society constructed what can be called a collective consciousness that materialize common beliefs such as religion into codes and rules (Crysler, 2003). In the case of the traditional Arab-Islamic built environments this can be evident in Islamic laws that governed the community. These laws constituted the underlying deep structure that were mapped through the transformation rules of fiqh into the surface structure of the urban

fabric of the traditional Muslim built environment. Crysler argues that the strength of this collective inner spirit is that it forms a protective barrier around the identity of societies.

6.3 Future Potential

spirit (Crysler, 2003).

Therefore, resilience of traditional built environments is linked to the endurance of this

The following aspects can be further studied and explored in future research, especially within the Middle East local contexts.

6.3.1 Traditional and informal settlements Traditional and informal settlements are claimed to share a lot of aspects that can be explored in order to enhance our understanding of these built environments. In the following some of these aspects will be discussed briefly.

Biologically, Genotype is the "internally coded, inheritable information" carried by a living organism, holds the critical instructions that are used and interpreted by the cells to produce the "outward, physical manifestation", or Phenotype

Self-organization in spontaneous settlements Spontaneous settlements usually referred to in many developing countries as peripheral or informal settlements form an important portion of the urban growth of these cities (Barros & Sobreira, 2002). These settlements can be considered as complex subsystems embedded within complex urban system as Barros and Sobreira (2002) discussed briefly in the conclusion of their paper titled as â&#x20AC;&#x2DC;City of Slumsâ&#x20AC;&#x2122;. Barros and Sobreira demonstrate the role of self-organization of spontaneous informal settlements in the socio political dynamics of the Third World cities. Barros and Sobreira argue that spontaneous settlements are constantly shaping and being shaped by self-organized process. This makes them a key element to understand the spatial pattern of Third World cities (Barros & Sobreira, 2002).

Cairo, Sao Paulo and other cities of the developing world have been studied as chaotic uncontrolled spatial entities due to the spread of spontaneous settlements. Barros and

Sobreira argue that spontaneous settlements play an important role in the city growth dynamics. These settlements that are considered as instability pockets can be vital for the

global stability of a system that is the city as they can absorb part of social instability mani-

fested in housing deficit. This assumption by Portugali mentioned by Barros and Sobreira backs up Turnerâ&#x20AC;&#x2122;s (1977) argument that spontaneous settlements can be an alternative solution for the problem of housing deficit in the developing world. This can prove true if it was viewed from the self-organization view (Barros & Sobreira, 2002).

Spontaneity and the future city Robert Neuwrith (2006) mentions a very interesting thought in his book called Shadow Cities that the way informal spontaneous settlements across many countries across the world have evolved is very similar to the way medieval old cities did. Further research can prove that the same assumption applies to the informal settlements and the medieval city of Cairo. This claim is validated by the observation brought up by David Sims (2010).

98 By looking at Figure 6.2, it shows how the urban fabric of informal developments on state desert land in Cairo we can see how the streets networks and building lots emerged spontaneously through interactions

(negotiations)

between

agents (settlers) and the mechanisms of the informal land market and the common need for access and circulation (interdependence) resulting in a local neighborhood pattern remarkably similar to the medieval urban fabrics (Sims, 2010, pp. 116-

cesses are autonomous; they rely on personal interactions. Informal ur-

Figure (6.1) Two urban fabrics that are separated by over nine hundred years. Top: Bab al-Wazir area in historic Cairo (developed in the eleventh century); bottom: Fustat Plateau area (developed in the 1980â&#x20AC;&#x2122;s). Source: (Sims, 2010)

ban development should be seen as a

117). Sims argues that informal pro-

normative, as a new form of urbani-

zation, as long as there are poor mi-

grating to the city and are not able to find a place to live (Sims, 2010).

Neuwrith introduces another provocative thought that squatters and the way they have developed can offer a solution for the future city as squatters proved extremely effective in the act of clearing the land and building on it. Their story of struggle and successes makes us view the land from another perspective than that of purchase and exchange value (Neuwirth, 2006).

6.3.2 Decoding /Encoding rules system If we are to understand the interactions between multiple agents, we need first to know the capabilities of individual agents (Holland, 1995). Holland sees that it can be heuristically useful to think of agent's behavior as a result of a set of â&#x20AC;&#x2DC;If-Thenâ&#x20AC;&#x2122; rules. In the context of the traditional built environment, this can be applicable also to the principles of

99 the traditional rules system. The rules can be decoded from the built environment in an â&#x20AC;&#x2DC;IfThenâ&#x20AC;&#x2122; format then encoded using computational models discussed in section 4.3.

6.3.3 Complex adaptive systems (CAS) and governance As previously mentioned in the course of this study, emergent higher level patterns can arise out of parallel complex interaction between local agents. It has been also noted that emergent systems are rule governed systems; their capacity for learning and growth and experimentation is derived from governing decentralized local rules. Acknowledging that giving up top-down control, giving systems a margin of freedom to govern themselves (bottom-up) as much as possible and letting it learn from and build on their experience is essential to understand emergence in CAS. Applying this framework to case studies from informal settlements around Cairo, several innovations in governance can be identified that demonstrate how CAS thinking can be valuable in utilizing governance to enhance the re-

silience of the built environment.

The CAS approach shifts the perspective on governance from the aim to control

change in resources through a rigid prescriptive socio-political systems, which is assumed

to be stable, to increasing the capacity of social-ecological systems to learn to live with and shape change and even find ways to transform into more desirable directions. Adaptive management of environmental resources presents a challenge to traditional government, with its reliance on bureaucratic procedures, the lengthy processes of legislative deliberation, and the often arbitrary nature of judicial decision making.

Conventional ideas about governance involve a top-down hierarchy under a single central controlling authority. In contrast, a CAS is characterized by interdependent network clusters under distributed control, with an open boundary and shared authority. The goals of agencies in traditional governance are ideally clear with defined problems. The goals in a collaborative CAS are various and changing. In conventional governance, planning is linear and the criterion for success is the attainment of policy goals. In a collaborative CAS, planning is nonlinear and the criterion for success is the realization of collective free action by the agents. In the long term, governance strategies for resilience may require a combination of strategies depending on the context (Booher & Innes, 2010). This emergent model of self-governance and self-organization can be more resonant with effective approaches to

100 adaptive management that enhance resilience for resource management than traditional government practices.

6.3.4 Traditional rules system in domestic context (residential scale) Shared social patterns and preferences of a culture are expressed in the house and the organization of its spaces. This makes it a product of collective identity. Dealing with social intercourse and spatial domains makes it difficult to study the house separately from the settlement or the city it is located in. the house needs to be studies as a part of a larger social and spatial system (Rapoport, 1969).

The house can be the most complex building, despite its domestic and small physical scale. A house can only be validly studied as a system of settings that certain system of activities occurs within (Rapoport, 1969). That makes it imperative to explore the open-

endedness or resilience of housing from a dwelling scale reaching to the settlement or

neighborhood scale including streets and outdoor spaces (Rapoport, 1990).

Most of the research previously mentioned in this study concerning spatial patterns and social structures is mostly conducted on the urban scale. Few of these studies were conducted on how dwellings embody and express socio-cultural conditions in their spatial configurations. An example of this is the empirical research on the significant relation between spatial and social structures (Hanson, Hillier, Rosenberg, & Graham, 1998). In this research, patterns of space were studied and how they are governed by certain conventions or ‘rules’ to reveal the essence of the house. Much fewer works were related to the context of the contemporary Arab built environments8. The analysis of domestic space organization can provide the link between design of dwellings and its social consequences.

Such as the PhD titled “Bi-polarity and Interface in the Spatial Organization of Cairo Apartments” (Eid, 1993). 8

101 The relation between traditional rules based on Islamic law and Complexity Theory studied and demonstrated in this dissertation can open up a new area of research to be explored at the domestic scale of the spatial organization of traditional houses. This kind of relation may be valuable to reveal the factors behind the resilience of these houses over a

long period of time and through various stages of use and diverse spectrum of users.

102

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