Co-creation: Space Reconfiguration by Architect & Agent Simulation Based Machine Learning by Anni Dai

Thank you Alessio Grancini

for the concept initiation and help

Kyle Koops

for all the hard works and support over last months and

Anna Ovchinnikova Olga Philippova Margarita Volkova Anastasia Shesterikova Zubin Tan

for all the hard work over diploma help week and more

Foreword: Architect’s Co-creation with Machine Learning

Programme Setup/Methods Agent Behaviour Machine Learning Training Principle AI Compliments

Archtectural Setup/Methods Timeline Housing Typology Wall Resolution

User Manual

20 Housing Precedents Into Agent Simulation Trained Result

Architect’s Co-creation with Machine Learning This essay is intended to briefly explore the theory of design methodology behind using agent simulation in architectural/urban design, and the use of machine learning in architectural / urban design’s implication on design scientific research’s history and future. It explores the plausibility to regard the Machine learning based Architectural/Urban design with agent simulation as one of the new generation design methods, and how it potentially changes the architectural/urban design process. This essay also serves as the concept statement of my diploma project.

Simulation as a medium in architectural/urban design To answer what is the medium of architectural/urban design, we first need to look at design as a discipline. According to Archer (1979), The third area in education, other than Science and Humanities, claims ‘technology and the fine, performing and useful arts’ (Archer, 1979, p19) without their scientific knowledge base or their history, philosophy and criticism. ‘The third area is the collected body of practical knowledge based upon sensibility, invention, validation and implementation.’ (Archer, 1979, p19) The naming of the third area is Design, which is defined as ‘the area of human experience, skill and understanding that reflects man’s concern with the appreciation and adaptation of his surroundings in the light of his material and spiritual needs.’ (Archer, 1979, p20) Design is aspirational and operational. What is the medium of architectural/urban design? Here again I’m referring to Archer (1979), ‘The essential language of Design is modelling. A model is a representation of something.’(Archer, 1979, p20) ‘Thus design activity is not only a distinctive process, comparable with but different from scientific and scholarly processes, but also operates through a medium, called modelling.’ (Archer, 1979, p18) Simulation works as one of the mediums of architectural/urban design. Banks et al. (2001) explained a simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. ‘The vocabulary and syntax of the modelling of ideas in the Design area can be conveyed through a variety of media such as drawings, diagrams, physical representations, gestures, algorithms.’ (Archer, 1979, p20) Simulation, as an evolution of the models of ideas over time with execution from computers, works as a ‘new’ medium in the architectural/urban design process. Computer simulation’s application in the architectural/design design process has been adopted for decades. In the book ‘Urban Dynamics’ by Jay W. Forreste, the dynamics of urban decay and revival was structured and modelled. It found out that ‘When a system theory takes shape as a simulation model, its behavior precipitates more discussion and brings out additional supporting and contradictory information that helps refine the theory.’ (Forrester, 1970, p9) In the late 1970s to early 1980s, the term space syntax was conceived at Barlett, UCL. The general idea is that spaces can be broken down into components, analyzed as networks of choices, then represented as maps and graphs that describe the relative connectivity and integration of those spaces. Space syntax has also been applied to predict the correlation between spatial layouts and social effects, applying modelling and simulation technologies in the design experience (Hillier, 1976). Michael Batty, Professor of Planning in the Bartlett, UCL, has been focussed on the development of analytical methods and computer models for simulating the structure of cities and regions (Wikipedia, 2021). More recently, shadow analysis, which is a study of shades and shadows cast by architecture modelled and simulated in computers, has been widely adopted in the architectural/urban design/planning process.

Agent behaviours’ role in design methodology What is design research’s relation to humanities? According to Bayazit (2004), Design research tries to answer the obligations of design to the humanities. ‘Cultural anthropology and its influence on design began during the 1950s. In the UK, the application of social psychology to design started in the 1960s. In Sweden, various ergonomics studies were made on housing, especially on bedrooms and other home spaces. In the UK, Loughborough was another center for scientific research related to ergonomics.’ (Bayazit, 2004, p23) Bayazit (2004) explained that during the 1960s, the interest of design methods had been shifted from hardware and form to the consideration of human needs, due to technological developments and the implication of mass production. Between 1960s-1970s, ‘The influence of systems analysis and systems theory on design established the grounds for the foundation of ‘systematic design methods’, which Horst Rittel later called ‘first generation design methods.’’(Bayazit, 2004, p18) ‘Ray Struder, whose very title ‘The dynamics of Behavior-Contingent Physical Systems’ summarized what they were all about. Design was to be ‘scientific’-struder was looking for a ‘unit of analysis in design measurable, in his words, against dimensions that are both relevant and empirically accessible.’ ‘The designer has to start by analyzing human behavior, from which he could derive ‘quantities, qualities and relationships.’’ (Bayazit, 2004, pp19-20) However, ‘First-generation design methods were simplistic, not mature enough, and not capable of meeting the requirements of complex, real-world problems.’ (Bayazit, 2004, p21) Between 1970s-1980s, according to Bayazit (2004), during what Horst Rittel referred to as second generation design methods, user involvement in design decisions and the identification of their objectives were the main characteristics. However, there were some obstacles in the application of participatory design in larger-scale projects, such as those in urban planning. What became of human or agent behaviour’s role in design methodology today ? The technological development enables simulation of agent, and the combination between design experience with agent simulation. Penn and Turner (2002) studied space syntax based agent simulation; they described an exosomatic visual architecture, based on space syntax visibility graphs, giving many agents simultaneous access to the same pre-processed information about the configuration of a space layout. Today, there is also agent based parametric semilogy whose goal ‘is to move from an intuitive participation within an evolving semiosis to an explicit design agenda that understands the design of a large scale architectural complex as an opportunity to design a new, coherent system of signification, a new artificial architectural language, without relying on the familiar codes found in the existing built environments.’ (Anon, 2021)

SPAN. (n.d.). SPAN. Urban Fiction. Available at: https://span-arch.org/ (Accessed 22 Nov. 2021). 2

Baldwin, E. (2019). AI Creates Generative Floor Plans and Styles with Machine Learning at Harvard. [online] ArchDaily. Available at: https://www.archdaily.com/918471/ai-creates-generative-floor-plans-and-styleswith-machine-learning-at-harvard.

del Campo, M., Carlson, A., & Manninger, S. (2020). 3D Graph Convolutional Neural Networks in Architecture Design.

Machine learning’s role in design scientific research What is design science? Bayazit (2004) referred to Vladimir Hubka and Ernst Eder’s definition, the term ‘design science’ is to be understood as a system of logically related knowledge, which should contain and organize the complete knowledge about and for designing. Looking back at the origin and history of scientific development in design research, Norbert Wiener played an important role. His idea ‘Cybernetics’ ‘became the model for rational behavior employed in economics, and obtaining information and making decisions using computer systems.’ (Bayazit, 2004, p23) ‘The study of human performance and man-machine relationship developed great momentum.’ (Bayazit, 2004, p23) Cornell University, MIT, the University of Sydney, Carnegie Mellon University, and the University of California were the leading roles in the design science and computer aided design (CAD) (Bayazit, 2004, p23). ‘Prefabricated building design, and research on coordinated building elements and the building layout optimization, were well-accepted research subjects in the universities as well as in the research centers.’ (Bayazit, 2004, p25) ‘Mosley developed one of the first layout optimization programs for hospital operating units.’ (Bayazit, 2004, p25) ‘There was a close relationship between design research and the developments in the IT field, especially in cognitive sciences, and “artificial intelligence” (AI) and expert systems.’ (Bayazit, 2004, p27) Marvin Minsky’s studies on AI researchers affected the development of studies on designers; Charles Eastman published an article related to intuitive bathroom design and, for the first time, focused on the designer’s behavior (Bayazit, 2004, p27). ‘Donald Schön at MIT opened a new paradigm in design research, and his book, Reflective Practitioner, did not seem to relate to computer science at first, but it actually was about the designing behavior of expert designers.’(Bayazit, 2004, p27) Machine learning as a part of artificial intelligence, has recently been used in architectural/urban design. Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data (Mitchell, 1997). By employing machine learning in the architectural/ urban design process, design automation is implied and thus brings both opportunity and threat to architects and the architectural design creative process. 3

There are a few examples of how machine learning is applied in architectural/urban design. Matias del Campo has been using machine learning in the architectural/urban design process, the work ‘Urban Fictions’ re-evaluate urban conditions with the aid of machine learning. ‘The Robot Garden’ combines research on machine vision and machine learning and is applied to architecture (SPAN, 2021). A recent project from Harvard used machine learning to explore the future of generative design, which is based on Generative Adversarial Neural Networks (GANs) (Baldwin, 2019). The examples are restricted with 2d images based, as the progress to 3d modelling in machine learning is still very much in the experimental stage. There are some studies that can demonstrate the progression in this field. The paper 3D Graph Convolutional Neural Networks in Architecture Design shows the training potential in 3d models (Campo, Carlson, and Manninger, 2020), which are primitive deformed meshes. It conveys styles but restricts direct usage in practical architectural design. Adoption of machine learning in architecture/urban design pushes forward the idea of design automation, which puts architects’ role in question. It can relate back to Donald Schön’s study on designer behaviour, which did not seem to relate to computer science back then, but here can be compared under the design automation discussion. Can machines replace architects by learning designer behaviours? And is machine learning, or design automation exempt from human/architect intervention? The author would like to briefly answer the question from one aspect but not try to form a comprehensive opinion. Tacit knowledge - as opposed to formal, codified or explicit knowledge—is knowledge that is difficult to express or extract, and thus more difficult to transfer to others by means of writing it down or verbalizing it. This can include personal wisdom, experience, insight, and intuition (Polanyi, 1958). There is tacit knowledge in humans or architects that can hardly be conveyed, which is an important characteristic of architects. Architect design not only through accumulation of architectural knowledge, but all the other experiences form over the years and transforms to one’s unique tacit knowledge. One can argue that machines can learn and therefore form tacit knowledge as well, as machine learning learns through past experiences. Here it is important to note that the database that machine learning is based on is created and structured by humans, which exempt machines from getting unwanted information from humans. The unwanted information might be part of the contribution to the machine’s tacit knowledge. However, with unstructured or unwanted information in the database, the learning curve can be unnecessarily long, and might end in unsuccessful training. The database has human intervention, therefore the experience the machine gains is limited and structured, and differs itself from human knowledge.

Reconfigure space using machine learning based on agent simulation Human behaviour study has played a significant and continuous role in design methodology. Baudrillard claims that our current society has replaced all reality and meaning with symbols and signs, and that human experience is a simulation of reality (Baudrillard, 1994). With technological development, simulation, which is a ‘new’ medium in architectural design, has been widely adopted and applied to human behaviour, which is agent simulation. Agent simulation is an architectural design medium and a

design method. Machine learning as part of contemporary design sciences, has in its nature relation with design research. ‘Mutual influences of information technologies and design research were the requirements of the era.’(Bayazit, 2004, p28) It makes sense to combine machine learning with agent simulation. It is worth noting that in this case, different from the conventional routine of design sciences that goes from design to analysis to redesign, such as shadow analysis or Karamba analysis, machine learning breaks the routine and adapts design according to analysis results automatically. It is in the author’s interest to find machine reconfiguring space automatically based on different agent simulation, and it has been experimented on the author’s diploma project. However, it is important to note that the virtue of the project does not lie in design automation, but the machine’s assistance to the architects in utilizing its particular strengths.

Anon, (n.d.). ABSTRACT – agent based semiology. [online] Available at: http://www.parametricsemiology. com/?page_id=204#:~:text=The%20aim%20of%20agent%20based [Accessed 22 Nov. 2021]. Archer, B. (1979). Design as a discipline. Design studies, 1(1), 17-20. Baldwin, E. (2019). AI Creates Generative Floor Plans and Styles with Machine Learning at Harvard. [online] ArchDaily. Available at: https://www.archdaily.com/918471/ai-creates-generative-floor-plans-and-styleswith-machine-learning-at-harvard. Baudrillard, J. (1994). Simulacra and simulation. University of Michigan press. Bayazit, N. (2004). Investigating design: A review of forty years of design research. Design issues, 20(1), 16-29. del Campo, M., Carlson, A., & Manninger, S. (2020). 3D Graph Convolutional Neural Networks in Architecture Design. Forrester, J. W. (1970). Urban dynamics. IMR; Industrial Management Review (pre-1986), 11(3), 67. Hillier, B., Leaman, A., Stansall, P., & Bedford, M. (1976). Space syntax. Environment and Planning B: Planning and design, 3(2), 147-185. J. Banks; J. Carson; B. Nelson; D. Nicol (2001). Discrete-Event System Simulation. Prentice Hall. p. 3. Mitchell, Tom (1997). Machine Learning. New York: McGraw Hill. Penn, A., & Turner, A. (2002). Space syntax based agent simulation. Springer-Verlag. Polanyi, M. (1958). Personal Knowledge: Towards a Post-Critical Philosophy. SPAN. (n.d.). SPAN. [online] Available at: https://span-arch.org/ [Accessed 22 Nov. 2021]. Tacit and Explicit Knowledge | Key Concepts in Information and Knowledge Management”. www.tlu.ee. Retrieved 2021-04-15. Wikipedia. (2021). Michael Batty. [online] Available at: https://en.wikipedia.org/wiki/Michael_Batty#cite_ note-13 [Accessed 22 Nov. 2021].

Programme Setup Agent Behaviour Machine Learning Working Principle

Agent Behaviour

A* Algorithm

The algorithm constantly calculates the avalable ways to reach the goal.

It chooses the closest route to reach the goal.

A* Heuristic Calculation with Manhattan Distance

A* Heuristic Calculation with Diagonal Distance

A* Heuristic Calculation with Euclidean Distance

Unblocked Blocked Target Source

To approximate the shortest path in real-life situations, likein maps, games where there can be many hindrances. We can consider a 2D Grid having several obstacles and we start from a source cell (colored red below) to reach towards a goal cell (colored green below)

Machine Learning Working Principle

Distance

The programme uses raycast 3d to detect the distance between people and walls.

Penalty

too far

too close Penalty is given when the walls are ‘too close’ or ‘too far from the people

Reward

Reward is given when the walls are within ‘good distance’ from the people Machine Learning works on a reinforcement learning basis, once it gets penalty, it ends episode; the more reward it gets, the more it learns from it. After training, machine learned the best position towards agents. The trained machine learning model is then applied to the precedents as experiments and tesification. 12

Time People have expected time for going from one room to another. This programmes also features adjusting room position based on expected time period of agents, and reconfigure space based on tme adjustments.

AI Compliments

(Room of different size with different amounts of agents inside, anf wall heights)

Room Size

Room Size is live updated according to the number of agents entering and the amount of time they spent in each room. The size is then accumulated and averaged throughout the training session. Small room with less people

Normally when a room regularly has less people, the room gets smaller. Big room with more people

When a room regularly has more people, the room gets bigger. Big room with less people

With control over weight, architect can control over the size of the room with the trained ML model. 15

Room Height

Room Height is live updated according to the number of agents entering and the amount of time they spent in each room. The height is then accumulated and averaged throughout the training session. It is also controlled to be no shorter than 2.7m and no taller than 8m.

Wall Generation When there are too many people enters the room, there is wall generation to separate the circulation.

Wall Deletion When less people are using the room, the added wall will be deleted.

Architectural Setup 20 Housing Precedents Wall Definition & Resolution Room Area Definition

The Housing Typoloogy Housing as a continuous typology spreads throughout architectural history, and across cultural boundaries. It is ideal as a reasearch subject for agent simulation study.

01_House of Vetti_Pompeii

19_Paper House_by Ban

Above are House of Vetti from 79AD, Roman Empire, and Paper House from 1993, Japan. They both share room typologies like bedroom, bath, living room, kitchen, etc.

Choice of Plan-like Architecture

The preference of plan-like architecture is because of its condensation of agent activities on the same floor level, which makes the training results easy to study and compare.

Due to the differences in housing styles from different times, certain periods only features buildings with 2 floors or more. In this case this project chooses their ground floor level as it is where most activities happens. 23

Wall Resolution What is the expected outcome of using different wall resolutions, why and how.

Mid Resolution

Low Resolution

High Resolution

User Manual

1 Choose a building

2 Type in number of agents

3 Play with weights

01_House of Vettii_Pompeii 02_Villa of the Mysteries_Pompeii 03_Villa Barbaro_by Palladio 04_Vaux-le-Vicomte_by Vau 05_Syon House_by Adam 06_Monticello_by Jefferson 07_Emo House_by Gandon 08_Watts Sherman House_by Richardson 09_Schindler House_by Schindler 10_The Farnsworth House_by Mies 11_Kaufmann House_by Neutra 12_Miller House_by Saarinen 13_Bailey House_by Koenig 14_Rosen House_by Ellwood 15_White U House_by Ito 16_Bridge House_by Ellwood 17_Koshino House_by Ando 18_Magney House_by Murcutt 19_Paper House_by Ban 20_Planar House_by Holl

01_House of Vettii_Pompeii Intro Agent Simulation Application Analysis Evaluation

Introduction

Photos/Original Plans

Introduction The House of the Vettii is a domus located in the Roman town, Pompeii, which was preserved by the eruption of Mount Vesuvius in 79 AD. The House of Vetti is located in region VI, near the Vesuvian Gate, bordered by the Vicolo di Mercurio and the Vicolo dei Vettii. The house is one of the largest domus in Pompeii, spanning the entire southern section of block 15. The plan is fashioned in a typical Roman domus with the exception of a tablinum, which is not included. There are twelve mythological scenes across four cubiculum and one triclinium. 29

01_House of Vettii_Pompeii

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline A roman residence, here it has been assumed that the occupants would consists of 5 masters, 10 staff and 3 guests. A typical day here involves the master & guest agents inhabiting the gardens, alae and dining spaces.

1 Seek

Master Waypoints

Wait

WanderTime

1-3

1-10

Atrium Small

✓ ✓ ✓

Kitchen

Alae

Garden

✓ ✓

5-30

15-60

5-10

Dining Room Staff

Painted Room

✓ ✓ ✓

5-10

360-480 X

3 X

2-5 X

Entry Atrium

Dining Room

Portcoed Courtyard Bedroom Pantry

01_House of Vettii_Pompeii

Seek

Guest Waypoints

Wait

WanderTime

Seek

Staff Waypoints

Wait

WanderTime

1-3

✓

1-3

1-10

5-10

✓ ✓ ✓

5-10

✓

5-10

✓

15-60

5-10

✓

1-2

✓

5-10

X X

✓

X X

X 3 Cleaning Staff 5

X 1-2 1-3

Master

Quantity: 5

ENTRANCE

MORNING

PORTICOED ROOM

GARDEN

ALAE

DINING ROOM

ATRIUM

DINING ROOM

PORTICOED ROOM

LUNCH

PORTICOED ROOM

ALAE

DINING ROOM

EVENING

DINING ROOM

Staff

BEDROOM

Quantity: 10

ENTRANCE

MORNING

PANTRY

COOKING

SERVING

KITCHEN

DINING ROOM

EVENING

LUNCH

KITCHEN

PANTRY

COOKING

SERVING

KITCHEN

DINING ROOM

CLEANING

KITCHEN

Guest

STAFF CLEANING STAFF CLEANING

PANTRY

COOKING

SERVING

KITCHEN

DINING ROOM

KITCHEN

Quantity: 3

ENTRANCE

ATRIUM

SMALL ATRIUMS

PAINTED ROOM

DINING ROOM

01_House of Vettii_Pompeii

ATRIUM

9 6

6 7

7 6

8 6

10 11

7 6

4 5

9 6

6 7

8 6 9

6 6

1 Painted room 2 Porlicoed Courtyard 3 Bedroom 4 Pantry 5 Kitchen 6 Alae 7 Atrium 8 Garden 9 Dining room 10 Fauces 11 Vestibule 01_House of Vettii_Pompeii

9 6

6 7

7 6

8 6

10 11

7 6

3 1

3 7 6 10 7

7 9 6

7 6 6

1 Painted room 2 Porlicoed Courtyard 3 Bedroom 4 Pantry 5 Kitchen 6 Alae 7 Atrium 8 Garden 9 Dining room 10 Fauces 11 Vestibule 01_House of Vettii_Pompeii

9 6

6 7

7 6

8 6

7 6

10 11

4 5

6 7

7 6

8 6 9

7 6

1 Painted room 2 Porlicoed Courtyard 3 Bedroom 4 Pantry 5 Kitchen 6 Alae 7 Atrium 8 Garden 9 Dining room 10 Fauces 11 Vestibule 01_House of Vettii_Pompeii

Room Weights

Room Area & Ratio 1 Original Ratio

Fauces A Fauces B Atrium A Atrium B1 Atrium B2 Atrium Cl Atrium C2 Atrium C3 Dining Room A Dining Room B Garden

Area 10.20 10.20 493.39 27.50 103.86 7.90 7.75 45.50 24.39 18.79 342.44

Kitchen Pantry Painted Room A Painted Room B

23.21 9.30 55.94 40.95

Vestibule Alae A Alae B1 Alae B2 Alae B3 Alae C Alae D Alae E Alae F Alae G Alae H Alae I Bedroom 1 Bedroom 2 Small Porticoed Courtyard

10.20 8.35 8.18 43.33 20.04 0.14 16.01 14.60 9.57 10.15 15.49 8.95 20.10 14.29 44.09

Total

1478.58

01_House of Vettii_Pompeii

0.73

0.08

0.17

Low Resolution Area Ratio 40.79459 23.69239 489.5217 29.22878 101.838 0.77 7.9991895 7.8103175 43.37178 31.69007 9.688716 335.0382

Mid Resolution Area Ratio 13.30695 3.328205 518.6948 27.62382 117.734 0.07 6.455952 10.66912 41.59792 24.32861 18.0242 189.0905

High Resolution Area Ratio 10.58383 2.347764 502.1397 30.04718 105.6522 0.75 7.556865 7.511086 41.93458 29.31712 21.59538 194.9059

20.55762 9.573627 53.85075 42.03259

18.93 9.627065 63.47569 51.39807

16.03081 5.783739 12.70457 13.46982

23.69239 6.860242 15.7988 46.83247 21.32368 14.20898 7.489612 14.55497 11.38238 8.853458 15.54815 8.865943 18.25876 14.71723 7.354891

1586.469

0.03

0.18

16.75864 8.337369 12.77172 37.95076 12.08392 9.248549 12.89059 13.96803 9.18389 9.992794 17.13735 7.733049 23.19773 20.09423 46.91027

1371.359

0.01

0.18

11.80665 6.987481 11.0901 40.69081 16.39327 15.25462 11.2255 14.58759 9.105927 10.1299 16.41477 9.086777 25.90161 14.40357 43.21553

0.03

0.2

1259.257

02_Villa of the Mysteries_Pompeii Intro Agent Simulation Application Analysis Evaluation

Introduction

Photos/Original Plans

Introduction

The Villa of the Mysteries (Italian: Villa dei Misteri) is a well-preserved suburban ancient Roman villa on the outskirts of Pompeii, southern Italy. It is famous for the series of exquisite frescos in one room, which are usually thought to show the initiation of a young woman into a Greco-Roman mystery cult.

Agent Behaviour Outline

A roman residence, here it has been assumed that the occupants would consists of 15 masters, 20 staff and 10 guests. A typical day here involves the master & guest agents inhabiting the gardens, cubliculums, dining and bathing. While staff serve. 43

02_Villa of the Mysteries_Pompeii

Agent Simulation

2 Seek Entry Secondary Enrty Tablinum Cubliculum Triclinium Room with painting Apotheca Dieta Portico Rustic Room Rustic Cubic Atrium Daytime Cubic Large Cubic Kitchen Court Kitchen Stores Kitchen Oven Corridor Passage Mosaic Room Apside Hall Wine Cellar Planting Latrine Farming Tools Side Access Room with Cast Body Tepidarium Perstyle Garden Changing Laconium Servants Quart

✓ X

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ X

✓ ✓ X X X X X X X

✓ X X

✓ X X X

✓ ✓ ✓ ✓ X

Master Wait Waypoints WanderTime 1-3 X X X X X X 5 5-10 360-480 2 1-3 15-60 2 5-10 X 3 5-10 X 3 1-2 15-60 2 5-10 X 5 5-10 X 3 5-10 X X X X 5 5-10 X 3 15-60 X X X X X X X X X X X X X X X X X X X X X 15-60 X X X X X X X X 3-15 X X X X X X X X X X X 30-60 X X X 5 5-10 5-10 X X 10-30 X X X X X

02_Villa of the Mysteries_Pompeii

Seek

✓ ✓ ✓ X

✓ ✓ X

✓ ✓ ✓ ✓ ✓ X X X X X X X X X X X

✓ X X X

✓ ✓ ✓ ✓ X

Guest Wait Waypoints WanderTime Seek 1-3 X X ✓ 1-3 X X X 1 5 5-10 X X X X X 15-60 2 5-10 ✓ X 3 5-10 X X X X X 15-60 2 5-10 X X 5 5-10 X X X 5-10 X 360-480 3 2-5 X X 5 5-10 X X X X X X X X X X X X ✓ X X X ✓ X X X ✓ X X X X X X X X X X X X X X X X X X X X X X X X 3-15 X X ✓ X X X ✓ X X X X X X X X 30-60 X X X X 5 5-10 5-10 X X X 10-30 X X X X X X ✓

Staff Wait Waypoints WanderTime 1-3 X X X X X X X X X X X X 5 1-3 X X X X X X X X X X X X X X X X X X X X X X X X X X X X 5 1-10 X 3 1-2 15-60 X X X X X X X X X X X X 5 1-3 X 5 1-2 X X X 3-15 X X X 3 1-2 X X X X X X X X X X X 360-480

X X 3 Cleaning Staff 5

X X 2-5 1-3

Master

Quantity: 15

ENTRANCE

LATRINEC

APSIDAL HALL

CHANGING

LANCONIUM

TEPIDARIUM

CHANGING

LANCONIUM

RUSTIC ROOM

ROOM WITH PAINTING

APSIDAL HALL

TEPIDARIUM

CHANGING

RUSTIC ROOM

ROOM WITH PAINTING

APSIDAL HALL

TEPIDARIUM

CHANGING

RUSTIC ROOM

PERISTYLE GARDEN

CHANGING

ATRIUM

APOTHECA

PERISTYLE GARDEN

TEPIDARIUM

CHANGING

DIETA

PERISTYLE GARDEN

PORTICO

ATRIUM

RUSTE ROOM

TRICLINIUM-OECUS

RUSTIC ROOM

DIETA

RUSTE ROOM

TRICLINIUM-OECUS

RUSTIC ROOM

PERISTYLE GARDEN

DIETA

PERISTYLE GARDEN

PORTICO

PERISTYLE GARDEN

TEPIDARIUM

CHANGING

LANCONIUM

CHANGING

LANCONIUM

Staff

DAYTIME CUBIC

TABINUM

APOTHECA

DIETA

PERISTYLE GARDEN

TRICLINIUM-OECUS

CHANGING

RUSTIC ROOM

PERISTYLE GARDEN

LANCONIUM

CHANGING

LANCONIUM

TEPIDARIUM

DIETA

PERISTYLE GARDEN

DAYTIME CUBIC

TABINUM

CHANGING

UBILICULUM

DIETA

PERISTYLE GARDEN

Quantity: 20

ENTRANCE

COOKING

STAFF CLEANING

KITCHEN STORES

KITCHEN OVEN

FARMING TOOLS

TRICLINIUM-OECUS

KITCHEN OVEN

APSIDALHALL STAFF

KITCHEN STORES

KITCHEN COURT

TRICLINIUM-OECUS

KITCHEN COURT

APSIDALHALL STAFF

FARMING TOOLS

TRICLINIUM-OECUS

KITCHEN COURT

GARDENING

PERISTYLE GARDEN

KITCHEN OVEN

KITCHEN COURT

LATRINE

WINE CELLAR

KITCHEN OVEN

KITCHEN COURT

APSIDALHALL STAFF

STAFF CLEANING

PERISTYLE GARDEN

WINE CELLAR

KITCHEN STORES

STAFF QUARTERS

Guest

Quantity: 10

ENTRANCE

TABLINUM

APSIDAL HALL

ROOM WITH PAINTING

CHANGING

ATRIUM

TEPIDARIUM

RUSTICROOM

LANCONIUM

PORTICO

CHANGING

RUSTIC ROOM

02_Villa of the Mysteries_Pompeii

SECOND ENTRANCE

PERISTYLE GARDEN

LANCONIUM

PERISTYLE GARDEN

DIETA

LATRINE

CHANGING

PERISTYLE GARDEN

TEPIDARIUM

PORTICE

CHANGING

ATRIUM

RUSTIC CUBIC

TRICLINIUM-OECUS

RUSTIC ROOM

PERISTYLE GARDEN

DIETA

4 5 3

10 12 12 11

13 21

15 34

22 19 29

14 21

24 26

19 18

20 31

1 Side Access 2 Wine Cellar Access 3 Wine Hall 4 Servant Quarters 5 Rustic Cubliculum 6 Rustic Room 7 Farming Tools 8 Vestibule 9 Rustic Quarter 10 Cast of Body 11 Small Rustic Room 12 Kitchen Store 13 Kitchen Courtyard 14 Oven 15 Laconium 16 Tepidarium

02_Villa of the Mysteries_Pompeii

6 17

27 20

33 19

19 32 22

19 20

6 13

12 12

5 22

9 10 11

17 20

4 1

20 31

16 6

33 19

6 14

17 Mosaic Room 18 Atrium 19 Cubicilum 20 Portico 21 Peristyle Garden 22 Passage 23 Apsidal Hall 24 Ante Room 25 Apotheca Store 26 Diaela 27 Triclinium 28 Tablinum 29 Paytime cubliculum 30 Exedra 31 Plantings 32 Room with Painting

33 Oecus 34 Apodyterium

4 5 3

13 21

5 3

9 10 12 12 11

15 34

24 26

19 25

20 31

6 17 17 20

27 20

02_Villa of the Mysteries_Pompeii

22 19

6 14

4 1

27 20

17 20

20 31

22 19 31

16 6

15 34

6 14

10 12 12 11

33 Oecus 34 Apodyterium

4 5 3

13 21

15 34

8 6

10 12 12 11

17 20

19 28

22 19 31

16 6

6 14

22 23

10 12 12 11

6 14

13 21

22 23 25 26 20

16 19

19 25

19 19

22 19

20 31

28 30

17 17 20

20 27 20

02_Villa of the Mysteries_Pompeii

33 Oecus 34 Apodyterium

Room Weights

Room Area & Ratio 2

02_Villa of the Mysteries_Pompeii

Perstyle Garden Corridor A Corridor B Servant Quarters 1 Servant Quarters 2 Servant Quarters 3 Servant Quarters 4 Atrium A Atrium B Apsidal Hall Apisal Ante Triclinium Oecus Kitchen Courtyard 1 Kitchen Courtyard 2 Kitchen Passage Kitchen Store A Kitchen Store B Oven Tepidarium 1 Tepidarium 2 Lanconium Apodyterium

Original Area Ratio 278.47 10.91 6.41 6.37 10.16 12.23 12.34 83.61 47.66 31.76 25.43 32.52 0.3 29.09 20.5 48.5 6.39 12.83 12.32 5.77 14.96 5.12 3.48 1.76

Low Resolution Area Ratio 277.23 11.06 3.89 7.83 8.87 8.76 14.8 78.68 47.67 31.01 31.6 28.15 0.3 29.63 29.5 49.1 6.44 12.53 12.32 6.69 15.09 5.13 4.54 1.38

Mid Resolution Area Ratio 267.64 1.42 5.86 15.09 14.11 22.48 9.37 92.98 50.37 26.92 36.98 34.09 0.35 22.75 37.16 56.42 6.18 11.49 10.07 1.86 16.34 16.32 3.62 4.23

High Resolution Area Ratio 285.66 81.50 3.77 15.05 13.53 28.90 12.39 82.08 40.96 33.25 24.95 36.64 0.35 25.57 28.51 56.67 6.89 28.81 12.72 4.24 2.39 0.73 1.99 9.47

Cubliculum A Cubliculum B Cubliculum C Cubliculum D Cubliculum E Cubliculum F Cubliculum G Cubliculum H Cubliculum I Daytime Cubliculum Rustic Cubliculum A Rustic Cubliculum B Rustic Cubliculum C Large Cubliculum A Large Cubliculum B Large Cubliculum C Rustic Room A Rustic Room B Rustic Room C Rustic Room D Rustic Room E Small Rustic Room RusticQuarterAccess Mosaic Room A Mosaic Room B Room With Painting Wine Hall Wine Cellar Access 1 Wine Cellar Access 2 Wine Cellar Access 3 Diaeta Tablinum Vestibule 1 Vestibule 2 Vestibule 3

8.53 8.15 8.03 12.93 4.21 16.06 13.89 6.17 14.49 15.91 6.69 9.01 8.42 11.32 6.89 11.45 16.34 18.45 9.19 104.80 12.65 6.99 55.39 8.62 11.48 9.56 58.20 9.23 7.83 18.82 12.93 25.40 17.69 27.60 18.72

8.53 8.15 7.98 12.93 4.21

7.48 5.12 4.75 14.91 3.78 21.24 17.49 4.02 14.83 15.21 14.52 2.58 8.09 11.22 6.36 11.32 14.09 7.31 8.55 9.61 12.89 7.12 55.21 8.39 9.87 9.63 81.69 2.24 7.93 13.40 16.29 25.21 43.00 20.77 49.95

0.26

11.35 4.98 6.38 12.96 2.75 13.74 15.51 6.08 14.49 1.82 13.44 15.42 9.88 13.60 6.95 22.51 16.54 16.81 9.17 10.26 25.72 6.52 59.72 6.19 11.55 9.56 38.94 6.82 9.51 18.76 19.28 28.19 18.27 49.30 19.17

0.23

Exedra 1 Exedra 2 Apotheca Store A Apotheca Store B1 Apotheca Store B2 Latrine Farming Tools Plantings A Plantings B Plantings C Plantings D Portico Al Portico A2 Portico A3 Portico A4 Portico C Portico D Portico E Passage A Passage B Passage C Passage D Passage E Side Access 1 Side Access 2 Room with Cast of Body

86.08 19.49 8.31 10.36 10.36 8.43 22.47 52.93 59.78 144.13 173.37 27.79 42.19 20.05 158.54 29.37 40.00 15.80 16.22 10.48 6.68 5.80 5.46 11.72 12.90 6.95

0.38

79.57 4.93 8.25 9.77 9.77 8.66 22.55 44.80 33.22 187.77 130.09 30.13 50.22 12.50 152.26 33.15 13.71 13.05 14.62 16.00 6.46 5.66 4.36 38.83 6.49 6.92

0.4

Total

2336.39

0.26

15.46 8.30 4144.00 1d. 98954 7.21 7.95 8.42 7.93 8.87 11.67 16.47 19.10 10.00 127.92 12.65 8.14 52.42 8.61 11.47 9.80 80.74 1.71

0.26

19.0E1011 12.47 21.47 16.21 27005.00 11.38 991.00 19.97 8.39 11.38 11.24 10.37 528.00 54.62

0.43

167.17 33.25 53.14 0.42 18.19 133.20 38.43 35.07 15.80 16.15 10.46 4.73 6.04 667646.00 36.94 5.79 3.65

62.66 11.97 2.41 5.73 5.73 8.04 3.32 56.88 51.80 146.82 122.70 20.85 0.02 22.67 141.08 33.88 41.54 16.71 19.26 11.92 6.93 1.37 6.86 10.72 5.05 6.80

2360.81

2152.02

2332.05

03_Villa Barbaro_by Palladio Intro Agent Simulation Application Analysis Evaluation

Introduction

Photos/Original Plans

Introduction Villa Barbaro, also known as the Villa di Maser, is a large villa at Maser in the Veneto region of northern Italy. It was designed and built by the Italian Renaissance architect Andrea Palladio. The central block is flanked by two symmetrical wings. The wings have two floors but are fronted by an open arcade. Usually, Palladio designed the wings to provide functional accommodation for agricultural use. The Villa Barbaro is unusual in having private living quarters on the upper level of the barchesse (that is, the rooms behind the arcades of the two wings). 57

03_Villa Barbaro_by Palladio

Agent Simulation

Agent Behaviour Outline The ground floor has been considered, a total of 5 masters, 10 staff and 5 guests. The staff agent is dominant here, as the ground level is mostly agricultural stores and service rooms for the rest of the building. Master and guest agents visit the frecoes, bacchus room and nymphaeum for events.

3 Seek Nymph Stair Courtyard Servant Quarters Storage Lamproom Dogroom Selfportrait room Olymp Pictures Elena Freesrair Fourthroom Love Courtroom Bacchusroom Servant Corridor Corridor General room

Wait

✓ ✓ ✓ X X

✓ ✓ ✓ ✓ ✓ ✓ X

✓ ✓ X X

✓

03_Villa Barbaro_by Palladio

X 5-10 X X X X X X X X X X X X X X X

Master Waypoints WanderTime 5 1-15 X X 5 5-10 X X X X 10 1-2 3 1-2 5 1-5 5 1-5 5 1-5 10 1-5 X X 5 2-6 5 2-6 X X X X 5 1-2

Seek

Wait

✓ ✓ ✓ X X

✓ ✓ ✓ ✓ X

✓ ✓ ✓ X X X

✓

X 5-10 X X X X X X X X X 1-3 X X X X X

Guest Waypoints WanderTime Seek 5 1-15 ✓ X X ✓ 5 5-10 X X X ✓ X X ✓ 10 1-2 X 3 1-2 X 5 1-5 X 5 1-5 X X X X 10 1-5 ✓ X X X 5 2-6 X X X X X X ✓ X X X 5 1-2 X

Wait X 5-10 X 360-480 X X X X X X X X X X X X X

Staff Waypoints WanderTime 5 1-15 X X X X 3 2-5 3 1-2 X X X X X X X X X X 10 1-5 X X X X X X 3 1-2 X X X X Cleaning Staff 5 1-3

Master

Quantity: 5

ENTRANCE

MORNING

COURTYARD

SELFPOTIART ROOM

PICTURE ELENA

DOG ROOM

BUCCUSROOM

LOVECOURT ROOM

FREE STAIRS

NYMPH

GENERAL ROOM

LUNCH

COURTYARD

SELFPOTIART ROOM

DOG ROOM

PICTURE ELENA

BUCCUSROOM

FREE STAIRS

LOVECOURT ROOM

GENERAL ROOM

NYMPH

EVENING

COURTYARD

SELFPOTIART ROOM

DOG ROOM

PICTURE ELENA

BUCCUSROOM

LOVECOURT ROOM

FREE STAIRS

NYMPH

GENERAL ROOM STAIR

Staff

Quantity: 10

ENTRANCE

MORNING

STAIR

STAFF CLEANING

STORAGE

DOG ROOM

STAFF CLEANING

LUNCH

SERVANT CORRRIDOR

FREE STAIRS

NYMPH

STORAGE

EVENING

SERVANT CORRRIDOR

FREE STAIRS

Guest

STAFF QUARTERS

Quantity: 5

ENTRANCE

MORNING

FOURTHROOM

STAIR

EVENING

LUNCH

SELF PORTAIL ROOM

NYMPH

03_Villa Barbaro_by Palladio

COURTYARD

DOGROOM

PICTURE ELENA

LOVE COUTROOM

FREE STAIRS

BACHUSROOM

OLYMP

NYMPH

FOURTHROOM

LAMPROOM

1 5

4 12

10 3

12 13

1 5

6 4

10 3

12 13

1 Store 2 Servants Quarter 3 Corridor 4 Free Stair 5 Pictures Elena Caliari 6 Generic Room 7 Dog Room 8 Olymp 9 Lamp Room 10 Self Portrait Room 11 Nymphaeum 12 Stair 13 Fourth Room 14 Bacchus Room 15 Love Court Room 16 Courtyard

03_Villa Barbaro_by Palladio

1 5

4 12

10 3

12 13

1 5

6 4

10 3

12 13

03_Villa Barbaro_by Palladio

1 5

4 12

10 3

12 13

1 5

6 4

10 3

12 13

03_Villa Barbaro_by Palladio

Room Weights

Room Area & Ratio 3 Original Area Ratio

Nymphaeum 2

386.55

Low Resolution Mid Resolution High Resolution Area Ratio Area Ratio Area Ratio 3.3 2.81 3.25 115.87 21.9 25.14 87.52 76.2 79.67 0.27 0.37 0.36 79.91 67.1945 72.33 2.86 2.91 4.17 20.17 21.14 20.87 81.78 108.63 95.92 403.24 290.16 385.82

Courtyard 1

275.06

268.35

212.36

Couttyard 2

275.06

317.4956

226.91

Fourth Room 1

41.94

Servant Corridor A1

Samara Corridor A2

21.75

Servant Quarter A

77.62

Servant Quarter B

77.62

Servant Corridor B1

Servant Corndor B2

21.75

Nymphaeum 1

188.62

Fourth Room 2

12.72

Fourth Room 3

12.72

Corridor A

45.25

0.36

5.78

0.44

11 13.09

75.61

0.44

38.72

16.96 11.49

Corridor B

45.25

47.49

45.56

Free Stair A

56.99

54.58

52.08

Free Stair B

56.99

62.04

50.83

Stair A

4.38

6.69

Stair B

5.99

7.59

Lamp Room

13.06

12.32

10.8

Bacchus Room

20.12

22.7

8.62

Love Court Room

20.12

14.29

3.79

Olymp

20.5

17.44

20.02

Dog Room

13.06

12.47

13.06

Generic Room A1

15.43

14.94

Generic Room A2

23.75

Generic Room B1

15.43

Generic Room B2

23.75

23.53

Storage Room A1

36.08

36.91

Storage Room A2

34.03

35.84

Storage Room B1

36.08

34.28

Storage Room B2

34.03

36.3

Self Portrait Room

24.93

25.77

Pictures of Elena Cailari

24.93

27.67

21.09 28.22 0.33 23.52 36.1 49.84 73.6 31.15 65.53 11.8

Total

1891.332

1887.672

1834.06

03_Villa Barbaro_by Palladio

28.48

0.19

19.65

0.4

45.38

0.17

0.21

263.11 280.96 52.9 14.15 12.67 43.09 42.45 48.04 99.15 2.57 6.63 12.88 19.69 15.92 19.82 5.29 27.56 37.03 23.82 28.1 29.67 32.44 103.48

0.39

0.24

98.84

2190.55

04_Vaux-le-Vicomte_by VauIntro Agent Simulation Application Analysis Evaluation

Introduction

Photos/Original Plans

Introduction The Château de Vaux-le-Vicomte (English: Palace of Vaux-le-Vicomte) is a Baroque French château located in Maincy, near Melun, 55 kilometres (34 mi) southeast of Paris in the Seine-et-Marne department of Île-de-France. The château is situated near the northern end of a 1.5-km long north-south axis with the entrance front facing north. Its elevations are perfectly symmetrical to either side of this axis. Somewhat surprisingly the interior plan is also nearly completely symmetrical with few differences between the eastern and western halves. The two rooms in the center, the entrance vestibule to the north and the oval salon to the south, were originally an open-air loggia, dividing the château into two distinct sections. 71

04_Vaux-le-Vicomte_by VauIntro

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline The ground floor has been considered, a total of 8 masters, 5 staff and 5 guests. The master behaviour is that of a resident, moving between cabinets and chambers as one would on a normal day. Guests are entertained in the Grand Salon, the staff agent serves the master and guest.

4 Seek Entry Grand Salon Chamber Cabinet Stair Coste De La Cour Garde Robe Bain

✓ ✓ ✓ ✓ ✓ ✓ X

✓

Master Wait Waypoints WanderTime 1-2 X X 15-60 2 5-10 360-480 3 2-5 15-60 3 5-10 5-10 X X X 5 5-10 X X X 3-15 X X

04_Vaux-le-Vicomte_by VauIntro

Seek

✓ ✓ ✓ ✓ ✓ ✓ X X

Guest Wait Waypoints WanderTime Seek 1-2 X X X 15-60 2 5-10 ✓ 360-480 3 2-5 ✓ 15-60 3 5-10 X 5-10 X X ✓ X 5 5-10 X X X X X X X X X

Wait X X 360-480 X 5-10 X X X

Staff Waypoints WanderTime X X 4 1-2 3 2-5 X X X X X X X X X X Cleaning Staff 5 1-3

Master

Quantity: 8

ENTRANCE

MORNING

GRAND SALON

BAIN

LUNCH

COSTE DE LA COUR

CABINET

STAIRS

GRAND SALON

BAIN

EVENING

COSTE DE LA COUR

CABINET

STAIRS

CABINET

CHAMBER

GRAND SALON

Staff

STAIRS

Quantity: 5

ENTRANCE

STAIR

GRAND SALON STAFF

STAFF CLEAN

LUNCH

STAFF CLEAN

MORNING

STAIRS

EVENING

CHAMBER

GRAND SALON

Guest

Quantity: 5

ENTRANCE

STAIR

04_Vaux-le-Vicomte_by VauIntro

CABINET

GRAND SALON

COSTE DE LA COUR

CABINET

STAIRS

CHAMBER

10 11

15 13

24 25

18 20

10 11

24 25

1 Garderobe C 2 Stair E 3 Chamber F 4 Garderobe A 5 Chamber C 6 Stair A 7 Cabinet B 8 Chamber B 9 Anti Chamber B 10 Cabinet H 11 Stair B 12 Vestibule 13 Stairs C 14 Grand Salon 15 Cabinet G 16 Anti Chamber A

04_Vaux-le-Vicomte_by VauIntro

17 Chamber D 18 Chamber E 19 Garderobe B 20 Stair D 21Cabinet E 22 Cabinet F 23 Bains 24Chamber A 25 Cabinet A 26 Coste De La Cour

10 11

15 13

24 25

18 20

5 4

24 25

04_Vaux-le-Vicomte_by VauIntro

6 7

17 Chamber D 18 Chamber E 19 Garderobe B 20 Stair D 21Cabinet E 22 Cabinet F 23 Bains 24Chamber A 25 Cabinet A 26 Coste De La Cour

10 11

15 13

24 25

10 11

8 7

04_Vaux-le-Vicomte_by VauIntro

17 Chamber D 18 Chamber E 19 Garderobe B 20 Stair D 21Cabinet E 22 Cabinet F 23 Bains 24Chamber A 25 Cabinet A 26 Coste De La Cour

Room Weights

Room Area & Ratio 4

Grand Salon Vestibule 1 Vestibule 2 Coste De La Cour Anti Chamber A AnnChamber13

Low Resolution Original Area Ratio Area Ratio 278.83 281.12 57.90 59.76 133.50 1.34 0.52 0.52 312.96 297.31 148.35 153.95 148.35 40.53

Chamber A Chamberf Chamber C Chamber D Chamber E Chamber F cabinet A Cabinet B Cabinet E Cabinet F Cabinet G Cabinet H

116.80 116.80 92.92 92.92 58.33 58.33 52.52 30.14 22.66 11.39 33.67 33.67

Bains Caue A Cane B Garderobe A Garderobe 13 Garderobe C Slag A Stair B Stair C Stair D Stair E

14.71 6.78 6.78 48.77 18.48 18.48 22.38 50.02 50.02 18.58 18.58

Total

2073.64

04_Vaux-le-Vicomte_by VauIntro

0.34

0.13

117.90 85.17 112.10 55.68 55.99 70.42 50.82 21.15 20.35 11.01 64.10 49.00 14.74 7.09 3.08 54.26 16.73 2.10 27.43 0.56 52.72 26.95 3.75 1757.11

Mid Resolution High Resolution Area Ratio Area Ratio 289.75 315.2 39.02 34.28 99.04 117.24 0.53 0.48 326.17 376.94 103.99 114.28 150.38 138.39

0.39

123.74 117.84 101.48 95.2 30.38 58.33 5.35 31.45 66.53 6.5 37.95 26.84

0.37

0.06

0.13

39.29 8.73 12.97 18.99

12.75 4.08 15.16 52.33 18.98 19.71 3.89 50.38 54.6 46.9 21.25

2151.21

2010.29

129.78

131.7 98.66 60.75 59.98

0.34

148.87 51.28 40.22 43.61 8.04 50.19 35.54 1.1

4.6 7.19 9.68 20.06

0.13

8.26 9.6

05_Syon House_by Adam Agent Simulation Application Analysis Evaluation

Introduction

Photos/Original Plans

Introduction yon House is the west London residence of the Duke of Northumberland. A Grade I listed building,it lies within the 200-acre (80 hectares) Syon Park, in the London Borough of Hounslow. The family’s traditional central London residence had been Northumberland House, now demolished. The eclectic interior of Syon House was designed by the architect Robert Adam in the 1760s. yon House’s exterior was erected in 1547 while under the ownership of the 1st Duke of Somerset. Syon’s current interior was designed by Robert Adam in 1762 under the commission of the 1st Duke and Duchess of Northumberland. 85

05_Syon House_by Adam

Agent Simulation

Agent Behaviour Outline A total of 8 masters, 16 staff and 10 guests. The master agent is a resident. Guests and master agents are entertained in the dining halls and drawing rooms. 5 Seek Entry Antiroom A Antiroom B Antiroom C Dining Room Drawing Room Long Gallery Anti Chamber Closet A Closet B Closet C Bed Chamber Dressing Room A Dressing Room B Writing Room Staircase to Mezz Powder Room Powdering Room Rotunda Service Stair A Service Stair B Private dining Grand Stair

05_Syon House_by Adam

Wait X X X X

✓ ✓ ✓ X X X

✓ X

✓ X X

✓ ✓ X X

✓ ✓

X X X X 15-60 X X X X X X X X X X X X 1-3 X X X 15-60 X

Master Waypoints WanderTime X X X X X X X X X X 3 5-30 3 5-30 X X X X X X 1 1-5 X X 2 1-15 X X 2 30-60 X X X X X X 3 1-3 X X X X X X 2 1-3

Seek

✓ ✓ ✓ X

✓ ✓ ✓ X X X X X X

✓ X X X X

Guest Wait Waypoints WanderTime Seek 1-3 X X X X 3 5-10 X X 3 15-60 X X X X X 15-60 X X ✓ X 3 5-30 X X 3 5-30 X X X X X X X X ✓ X X X ✓ X X X X X X X X X X X X X 1 15-60 X X X X X X X X X X X X X X X X X X 3 1-3 X X X X ✓ X X X ✓ X X X ✓ X X X X

Wait X X X X X X X X X X X X X X X X X X X X X 15-60 X

Staff Waypoints WanderTime X X X X X X X X 5 1-3 X X X X X X 1 1-5 1 1-5 X X X X X X X X X X X X X X X X X X 1 1-3 1 1-3 X X X X Cleaning Staff 5 1-3

Master

Quantity: 8

ENTRANCE

MORNING

GRAND STAIR

DRESSING ROOM

CLOSET C

WRITING ROOM

ROTUNDA

POWDERING ROOM

GRAND STAIR

LONG GALLERY

EVENING

LUNCH

GRAND STAIR

DRESSING ROOM

CLOSET C

POWDERING ROOM

GRAND STAIR

WRITING ROOM

ROTUNDA

CLOSET C

DRESSING ROOM

POWDERING ROOM

LONG GALLERY

GRAND STAIR

WRITING ROOM

ROTUNDA

GRAND STAIR

LONG GALLERY

Staff

Quantity: 16

ENTRANCE

STAFF CLEANING

MORNING

SERVICE STAR A

CLOSET A

CLOSET B

STAFF CLEANING

SERVICE STAR A

CLOSET A

CLOSET B

LUNCH STAFF PRIVAT DINING

SERVICE STAR A

CLOSET A

PRIVAT DINING ROOM

EVENING CLOSET A

PRIVAT DINING ROOM

SERVICE STAIR A

DINING ROOM

PRIVAT DINING ROOM

SERVICE STAR A

CLOSET A

DINING ROOM

Guest

SERVICE STAR A

Quantity: 10

ENTRANCE

ARRIVAL

LEAVING

ROTUNDA ENTRANCE HALL

ANTI ROOM A

LONG GALLERY ENTRANCE HALL

ANTI ROOM B

POWDERING ROOM

05_Syon House_by Adam

DRESSING ROOM

DINING ROOM

DRAWING ROOM

ROTUNDA

LONG GALLERY

12 10 6

14 15 17

4 3

2 1

19 18 20

12 10 6

14 15 17

4 3

2 1

19 18 20

1 Grand stair 2 AntiRoom C 3 Powedering Room 4 Closet C 5 Dressing Room 6 Anti Chamber 7 Bed Chamber 8 Dressing Room B 9 Staircase to Mezzanine 10 Long Gallery 11 Closet A 12 Closet B 13 Powder Room 14 Writing Room 15 Drawing Room 16 Area A

05_Syon House_by Adam

17 Area B 18 Dining Room 19 Rotunda 20 Private Dining 21 Area C 22 Area D 23 Service stair B 24 Antiroom A 25 Entrance Hall 26 Antiroom B 27 Service stair A

12 10 6

14 15 17

4 3

2 1

19 18 20

12 10 6

14 15 17

4 3

2 1

19 18 20

05_Syon House_by Adam

17 Area B 18 Dining Room 19 Rotunda 20 Private Dining 21 Area C 22 Area D 23 Service stair B 24 Antiroom A 25 Entrance Hall 26 Antiroom B 27 Service stair A

12 10 6

14 15 17

4 3

2 1

19 18 20

12 10 6

14 15 17

4 3

19 18 20 21

05_Syon House_by Adam

17 Area B 18 Dining Room 19 Rotunda 20 Private Dining 21 Area C 22 Area D 23 Service stair B 24 Antiroom A 25 Entrance Hall 26 Antiroom B 27 Service stair A

Room Weights

Room Area & Ratio 5

Service Stair A Service Stair B Grand Stair A Grand Stair B Entrance Hall Stair Mezzanine A Stair Mezzanine B

Original Original Original 6.95 6.07 15.14 50.10 0.17 160.76 20.69 20.69

Low Resolution Result Result 6.65 6.07 12.32 42.34 0.16 166.38 21.00 28.68

AntiRoom A AntiRoom B AntiRoom C Long Gallery Closet A Closet B Closet C AntiChamber Bed Chamber Dressing Room A Dressing Room B Powdering Room Rotunda

63.72 84.59 9.54 161.37 8.41 9.71 6.40 30.16 30.93 20.36 34.01 15.73 556.46

0.65

63.35 90.74 9.79 20.15 8.74 11.82 8.05 29.55 31.63 21.49 32.96 24.99 562.57

0.65

Writing Room Drawing Room Private Dining Dining Room

27.33 80.43 51.79 112.08

0.17

27.74 93.64 70.95 103.79

0.17

Total

1583.51

05_Syon House_by Adam

1674.54

Mid Resolution Result Result 4.91 6.07 21.62 52.37

0.19

161.09 20.10 30.16

61.86 86.14 41.25 173.77 7.83 9.50 4.24

0.62

32.01 30.93 19.97 14.18

High Resolution Result Result 7.33 6.84 37.20 2.48 0.17 165.36 41.49 29.19 41.28 84.59 10.96 163.02 8.84 10.61 6.72 30.58 29.39 18.14 35.34 16.91 651.25

14.53 554.35

104.52

11.59 91.46 77.83 106.78

1621.3

1653.9

29.60 87.99 50.09

0.66

0.17

0.16

06_Monticello_by Jefferson Agent Simulation Application Analysis Evaluation

Introduction

Photos/Original Plans

Introduction

Monticello was the primary plantation of Thomas Jefferson, the third president of the United States, who began designing Monticello after inheriting land from his father at age 26. Located just outside Charlottesville, Virginia, in the Piedmont region, the plantation was originally 5,000 acres (20 km2), with Jefferson using the labor of enslaved African people for extensive cultivation of tobacco and mixed crops, later shifting from tobacco cultivation to wheat in response to changing markets. Jefferson designed the main house using neoclassical design principles described by Italian Renaissance architect Andrea Palladio and reworking the design through much of his presidency to include design elements popular in late 18th-century Europe and integrating numerous ideas of his own. 99

06_Monticello_by Jefferson

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline The ground floor has been considered, a total of 4 master agents who are behaving as residents on a typical day. Guests agents attend for events, such as dinner or celebrations. Staff serve the resident day to day as well as the events where guests are included. The number of staff agents here is significant due to the presence of a plantation slavery. 6 Seek Entrance Hall Parlor East Portico West Portico Dining Room Tea Room South Square Room North Square Room North Octagonal Room Library Jeffersons Bedroom Jeffersons Cabinet South Passage North Passage Fireolace North Square WC South Square WC North Octagonal WC

Wait X

✓ ✓ ✓ ✓ ✓ X X X

✓ ✓ ✓ ✓ ✓ X X X X

X 15-60 15-30 15-30 15-60 15-30 X X X X 360-480 30-120 X X X X X X

Master Waypoints WanderTime X X 2 5-10 2 5-10 2 5-10 2 5-10 2 5-10 X X X X X X 3 15-60 3 2-5 X X

X X X X

Seek

✓ ✓ ✓ ✓ ✓ ✓ X X X

✓ X

✓ X X X

✓ ✓ ✓

Guest Wait Waypoints WanderTime Seek 1-5 X X X 15-60 2 5-10 ✓ 15-30 2 5-10 ✓ 15-30 2 5-10 ✓ 15-60 2 5-10 ✓ 15-30 2 5-10 ✓ 360-480 3 2-5 X 360-480 3 2-5 X 360-480 3 2-5 X X 3 15-60 X X X X X 30-120 X X X X X X ✓ X X X ✓ X X X ✓ 3-15 X X ✓ 3-15 X X ✓ 3-15 X X ✓

Wait X X X X X X X X X X X X X X X X X X

Staff Waypoints WanderTime X X 6 1-2 6 1-2 6 1-2 6 1-2 6 1-2 X X X X X X X X X X X X

Cleaning Staff 5

06_Monticello_by Jefferson

1-3

100

101

Master

Quantity: 4

ENTRANCE

MORNING EVENING

TEA ROOM

PALOR

JEFFERSON CABBINET

SOUTH PASS

DINING

PARLOR

EAST PORTICO

NORTH PASS

SOUTH PASS

WEST PORTICO

DINING

LUNCH

TEA ROOM

NORTH PASS

PALOR

JEFFERSON CABBINET

Staff

Quantity: 10

ENTRANCE

FIRE PLACE

MORNING

STAFF CLEANING

FIRE PLACE

STAFF CLEANING

EVENING

TEA STAFF

SOUTH PASS

PALOR STAFF

WEST PORTICO STAFF

EAST PORTICO STAFF PALOR STAFF

LUNCH

NORTH PASS

TEA STAFF

PALOR STAFF

WEST PORTICO STAFF

EAST PORTICO STAFF

DINING STAFF

FIRE PLACE

DINING STAFF

Guest

Quantity: 6

ENTRANCE

ARRIVAL

MORNING

TEA ROOM

LIBRARY

EVENING

JEFFERSON CABBINET

LUNCH

PARLOR

EAST PORTICO

WEST PORTICO

PARLOR

EAST PORTICO

BEDROOM 1

PARLOR

BEDROOM 2

DINING

BEDROOM 3

DINING NORTH OCT WC

NORTH SQ WCN

06_Monticello_by Jefferson

WEST PORTICO

ORTH SQ ROOM

NORTH SQ WCN

NORTH OCT ROOM

NORTH OCT WC

ORTH SQ WC

NORTH SQ ROOM

NORTH SQ WC

102

103

9 2

5 1

14 6

9 2

1 South Piazza 2 Jeffersons Cabinet 3 Library 4 Jeffersons Bedroom 5 Fireplace 6 South Passage 7 South Square Room 8 West Portice 9 Parlor 10 Enterance Hall 11 East Portico 12 Dinig Room 13 Tea Room 14 North passage 15 North Piazza 16 North Square Room

06_Monticello_by Jefferson

17 North Octagonal Room

104

105

9 2

5 1

14 6

4 5

06_Monticello_by Jefferson

17 North Octagonal Room

106

107

9 2

5 1

14 6

9 2

5 1

14 6

06_Monticello_by Jefferson

17 North Octagonal Room

108

109

Room Weights

Room Area & Ratio 6 Original Area Ratio 71.51 37.03 24.09 0.42 13.67

Low Resolution Area Ratio 87.98 38.53 31.01 0.46 13.71

Mid Resolution High Resolution Area Ratio Area Ratio 88.29 86.83 38.72 52.57 26.90 19.72 0.44 0.40 10.77

19.16 68.77

27.17 63.74

18.95

North Sq Room 1 North Sq Room 2 North Sq WC South Sq Rm 1 South Sq Rm 2 South Sq WC North Oct Rm 1 North Oct Rm 2 Fireplace 1 Fireplace 2 Fireplace 3

2.56 31.39 2.69 30.81 2.54 2.69 29.75 2.69 1.40 1.91 1.56

2.56 31.02 3.08 38.18 1.93 3.39 29.75 2.69 1.42 1.93 1.58

3.40

North Piazza 1 North Piazza 2 South Piazza North Passage 1 North Passage 2 South Passage Jeffersons Bedroom Jeffersons Cabinet Wood Place 1 Wood Place 2 East Portico West Portico

18.79 5.14 28.56 11.31 12.58 8.02 35.79 22.45 2.25 2.26 38.11 20.84

Total

550.33

Parlor Dining Room Library 1 Library 2 Tea Room Entrance Hall

06_Monticello_by Jefferson

0.19

0.39

18.78 2.01 28.56 13.78 10.10 7.91 27.82 14.86 2.69 2.26 38.11 20.84 567.58

14.29

14.39 56.51

67.22

25.02

0.04 33.43 2.62

0.20

2.69

0.20

38.15 3.70 1.13 1.81 1.65

11.97 22.96 13.34

5.83 7.80 24.94 24.92

0.42 2.05

38.15

0.19

29.62 7.77

28.05

0.33

2.50 31.90 2.60 30.34 2.62 2.68 31.27 2.67 4.20 1.90 1.56

0.34

29.04 10.45 12.57 8.49 36.33 23.20 2.45 2.27

23.29

40.65 32.72

580.14

585.06

0.40

110

111

07_Emo House_by Gandon Agent Simulation Application Analysis Evaluation

112

Introduction

Photos/Original Plans

Introduction Emo Court, located near the village of Emo in County Laois, Ireland, is a large neo-classical mansion. Architectural features of the building include sash-style windows, pavilions, a balustrade, a hipped roof, and a large dome. Inside the house, an octagonal entrance hall has doors in each of its four angles. Two of them really are entrances to other rooms. The others to give a balanced effect. A larger doorway leads to the rotunda (inspired by the Pantheon), a key feature of the mansion and also the way into two of the major rooms and out to the garden 113

07_Emo House_by Gandon

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline There are 5 master agents, 8 staff and 4 guests. The master agent is a resident undertaking daily behaviour, while guests are present occasionally for events and dining. The staff agents serve the master daily, as well as the events and undertake cleaning behaviours.

7 Seek Entrance Entrance Hall Library Dining Room Drawing Room Rotunda Stairwell Private Room Bathroom Storage Morning Room Kitchen Servant Stair Pantry Corridor

07_Emo House_by Gandon

Wait X

✓ ✓ ✓ ✓ X

✓ X X X

✓ X X X X

X X X 15-60 15-60 X X X X X 15-30 X X X X

Master Waypoints WanderTime X X 3 1-3 3 15-60 2 5-10 2 5-10 X X X X X 2 X X X X

X X X 5-10 X X X X

Seek

✓ ✓ X

✓ ✓ ✓ ✓ X X X

✓ X X X X

Guest Wait Waypoints WanderTime Seek 1-5 X X X X 3 1-3 X X X X X 15-60 2 5-10 ✓ 15-60 2 5-10 ✓ X 3 1-3 X X X 360-480 3 2-5 X 3-15 X X X X X X ✓ 15-30 2 5-10 ✓ X X X ✓ X X X ✓ X X X ✓ X X X X

Wait X X X X X X X X X X X X X X X

Staff Waypoints WanderTime X X X X X X 6 1-2 6 1-2 X X X X X X X X 3 1-2 3 1-2 5 5-10 3 X Cleaning Staff 5

1-2 X 1-3

114

115

Master

Quantity: 5

ENTRANCE

MORNING

LUNCH

ENTRANCE HALL

MORNING ROOM

LIBRARY

DINING ROOM

DRAWING ROOM

EVENING

DINING ROOM

DRAWING ROOM

STAIRWELL

Quantity: 8

Staff ENTRANCE

MORNING

STAFF CLEANING

EVENING

STAFF CLEANING

COOKING

STORAGE

PANTRY

SERVING

DRAWING STAFF

KITCHEN

MORNING STAFFK

ITCHEN

DINING STAFF

SERVING

COOKING

KITCHEN

PANTRY

SERVING

STORAGE

KITCHEN

DRAWING STAFF

KITCHEN

DINING STAFF

KITCHEN

LUNCH

COOKING SERVING

PANTRY

STORAGE

KITCHEN

DRAWING STAFFK

ITCHEN

SERVING

DINING STAFF

Quantity: 4

KITCHEN

Guest ENTRANCE

ARRIVAL

MORNING

DINING ROOM

ENTRANCE HALLM

ORNING ROOM

07_Emo House_by Gandon

BATHROOM

ROTUNDAB

ROTUNDA

ATHROOM

LUNCH

DRAWING ROOM

DINING ROOM

PRIVATE ROOM

DINING ROOM

LEAVING

DINNER

DRAWING ROOM

ENTRANCE HALLE

NTRANCE HALL

116

117

7 15

1 5

2 3

9 11 4

7 15

1 5

2 16

9 11 4

12 7

07_Emo House_by Gandon

1 Kitchen 2 Servant Stair 3 Corridor 4 Pantry 5 Dining Room 6 Private Room 7 Enterance 8 Rotunda 9 Enterance Hall 10 Library 11 Stairwell 12 Morning Room 13 Bathroom 14 Storage 15 Drawing Room Wing A 16 Drawing Room

17 Drawing Room Wing B

118

119

7 15

1 5

2 3

13 9

16 14

11 4

7 15

1 5

2 16

3 13

9 4

12 7

07_Emo House_by Gandon

17 Drawing Room Wing B

120

121

7 15

1 5

2 3

13 9

16 14

11 4

7 15

1 5

2 3

13 9

16 14

11 4

12 7

07_Emo House_by Gandon

17 Drawing Room Wing B

122

123

Room Weights

Room Area & Ratio 7

Drawing Room Drawing Room A Drawing Room B Morning Room Library Dining Room Private Room

Original Area Ratio 63.99 22.37 24.71 19.68 0.49 69.95 69.94 46.03

Low Resolution Area Ratio 50.73 32.62 42.92 13.27 0.49 96.44 73.16 38.98

Kitchen 1 Kitchen 2 Pantry

5.01 32.32 40.90

5.13 49.36 41.33

Stairwell Corridor 1 Corridor 2 Entrance 1 Entrance 2 Entrance Hall Rotunda Bathroom 1 Bathroom 2 Bathroom 3 Bathroom 4 Storage Servant Stair 1 Servant Stair 2

28.92 28.31 10.86 18.68 18.19 62.08 19.32 3.03 1.91 1.38 13.52 9.88 12.46 17.79

Total

646.73

07_Emo House_by Gandon

0.12

0.38

5.12 33.73 12.53 18.87 18.19 61.25 21.68 3.03 1.45 0.51 10.66 11.64 11.64 38.82 695.00

Mid Resolution Area Ratio 90.91 23.54 37.67 23.90

0.50

87.16 72.93 45.92 4.55

0.13

67.29

0.15

63.49 36.72 29.33 0.24 14.27 26.15 62.23

0.37

20.58 2.17 1.47

0.34

High Resolution Area Ratio 92.30 45.83 20.57 28.96 0.51 75.25 74.97 38.28 5.23 35.06 44.56 32.01 24.68 1.53 7.50 30.70 75.66 17.19 4.26 1.91

17.92

0.13 13.52 9.87 12.53 40.22

754.80

732.59

1.21 12.00

5.00 9.62

0.11

0.37

124

125

08_Watts Sherman House_by Richardson Agent Simulation Application Analysis Evaluation

126

Introduction

Introduction The William Watts Sherman House is a notable house designed by American architect H. H. Richardson, with later interiors by Stanford White. It is a National Historic Landmark, generally acknowledged as one of Richardson’s masterpieces and the prototype for what became known as the Shingle Style in American architecture. 127

08_Watts Sherman House_by Richardson

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline A total of 2 masters, 3 staff and 3 guests. The master agent undertakes typical acitvities of a resident. Guests attend events a dinner parties. While the staff agent serves the master and guests, undertaking cleaning activities.

8 Seek Entry Hall Dining Room Butlers Pantry Drawing Room Library Serving Room Stair Service Stair Terrace

Wait X X

✓ X

✓ X X

✓ X

✓

X X 15-60 X 15-60 X X X X X

Master Waypoints WanderTime X X X X 2 5-10 X X 2 5-10 X X X X

08_Watts Sherman House_by Richardson

Seek

✓ ✓ ✓ X

✓ X X

✓ X 3

X 1-5

X X

Guest Wait Waypoints WanderTime Seek 1-5 X X X X 5 1-2 X 15-60 2 5-10 ✓ X X X ✓ 15-60 2 5-10 ✓ X X X X X X X X X X X X X ✓ X X X X

Wait X X X X X X 1-2 X X X

Staff Waypoints WanderTime X X X X 6 1-2 3 1-2 6 1-2 X X X X X X X Cleaning Staff 5

X 1-3

128

129

Master

Quantity: 2

ENTRANCE

STAIR

MORNING

TERRACE

DRAWING ROOM

DINING

EVENING

LUNCH

DINING

DRAWING ROOM

DINING

STAIR

DRAWING ROOM

Staff

Quantity: 3

ENTRANCE

MORNING

SERVICE STAIR

BUTLERS PARTYS

SERVINGS

STAFF CLEANING

EVENING

ERVING ROOM

ERVING

DINING STAFF

STAFF CLEANING

SERVING

DRAWING STAFFD

INING STAFF

SERVING

COOKING

BUTLERS PENTRY

KITCHEN

SERVING ROOM

DRAWING STAFF

SERVING

DINING STAFF

LUNCH

SERVING

COOKING

BUTLERS PENTRY

SERVING ROOM

DINING STAFF

Guest

Quantity: 3

ENTRANCE MORNING

ARRIVAL

ENTRANCE

ENTRANCE HALL

DINING

DRAWING ROOM

08_Watts Sherman House_by Richardson

LUNCH

DINING ROOM

DRAWING ROOM

EVENING

LEAVING

DINING

STAIR

LEAVING

ENTRANCE

ENTRANCE HALL

130

131

10 1

4 3

10 1

4 6 3 7

1 Dining Room 2 Serving Room 3 Butlers Pantry 4 Service Stair 5 Stair 6 Vestibule 7 Enterance 8 Hall 9 Bay A 10 Library 11 Drawing Room 12 Bay B

08_Watts Sherman House_by Richardson

132

133

10 1

4 3

10 1

4 3

1 Dining Room 2 Serving Room 3 Butlers Pantry 4 Service Stair 5 Stair 6 Vestibule 7 Enterance 8 Hall 9 Bay A 10 Library 11 Drawing Room 12 Bay B

08_Watts Sherman House_by Richardson

134

135

10 1

4 3

10 1

4 3

1 Dining Room 2 Serving Room 3 Butlers Pantry 4 Service Stair 5 Stair 6 Vestibule 7 Enterance 8 Hall 9 Bay A 10 Library 11 Drawing Room 12 Bay B

08_Watts Sherman House_by Richardson

136

137

Room Weights

Room Area & Ratio 8

DINING ROOM DRAWING ROCA BUTLERS PANTRY SERVING ROOM I SERVING ROOM 2 SERVING ROOM 3

Original Area Ratio 71.15 43.67 20.38 0.35 1.33 2.66 18.75

Low Resolution Area Ratio 82.13 48.90 27.62 0.35 0.42 15.00 18.50

Mid Resolution High Resolution Area Ratio Area Ratio 80.26 94.65 42.82 42.03 21.12 21.50 0.38 0.37 2.19 20.50 3.54 6.63 18.54 38.10

HALL LIBRARY BAY A BAY B

72.10 28.77 15.93 9.26

66.01 31.54 16.18 7.23

71.88

ENTRANCE VESTIBULE TERRACE SERVICE STAIR STAIR 1 STAIR 2 STAIR 3

7.43 19.29 101.20 12.41 8.90 7.17 3.15

TOTAL

443.56

08_Watts Sherman House_by Richardson

0.28

0.35

7.43 25.03 101.20 13.49 4.92 7.88 1.83 472.91

0.28

28.77

15.93

0.30

70.57 33.80 12.75 12.60

0.30

7.20 21.94 73.98 13.23 9.46 5.20 2.23

0.31

8.39 2.09 2.67 65.71

0.35

19.93 0.58 3.63 12.58 456.40

430.93

138

139

09_Schindler House_by Schindler Agent Simulation Application Analysis Evaluation

140

Introduction

Photos/Original Plans

Introduction

The Schindler House, also known as the Schindler Chace House or Kings Road House, is a house in West Hollywood, California, Coordinates: 34.086362°N 118.372235°W designed by architect Rudolph M. Schindler. The Schindler House was such a departure from existing residential architecture because of what it did not have; there is no conventional living room, dining room, or bedrooms in the house. The residence was meant to be a cooperative live/workspace for two young families. The concrete walls and sliding glass panels made novel use of industrial materials, while the open floor plan integrated the external environment into the residence. 141

09_Schindler House_by Schindler

Agent Simulation

Agent Behaviour Outline The agent behaviour in the case study is non typically of other residences. There are a total of 5 masters and 2 guests. There are 3 studios which behave as living and working spaces. Therefore it has been assumed that dining takes place in either of these studios collectively and individually and sometimes with guests.

9 Seek Entrance Guest Bedroom Kitchen Cook Marian Chase Studio Bathroom Clyde Chase Studio Schindler Studio Courtyard Pauline Schindler Studio Nursery Patio Schindler Studio Bath Stair Garage Kitchen Eat

Wait X X

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

X X X 30-120 3-15 30-120 30-120 X 30-120 30-120 X 3-15 X X 15-60

09_Schindler House_by Schindler

Master Waypoints WanderTime X X X X 5 5-10 X X 2 1-5 X X X X 5 1-10 X X 5 1-5 5 1-5 2 1-5 3 X

1-2 X

Seek

✓ ✓ X

✓ X

✓ ✓ ✓ ✓ X X X X X

✓

Guest Wait Waypoints WanderTime Seek 1-3 X X 360-480 3 2-5 X X X 30-120 X X X X X 30-120 X X 30-120 X X X 5 1-10 30-120 X X X X X X X X X X X X X X X X X 15-60 X X

Wait

Staff Waypoints

WanderTime

142

143

Master

Quantity: 5

ENTRANCE

MORNING

SHINDLER STUDIO BATH

KITCHEN COOK

BATHROOM

KITCHEN COOK

KITCHEN EAT

PATIO

COURTYARD

GARAGE

SHINDLER STUDIO BATH

KITCHEN EAT

BATHROOM

EVENING

STAIR

CLYDE CHASE STUDIOP

CLYDE CHASE STUDIO

LUNCH

BATHROOM

PAULINE SHINDLER STUDIO

SHINDLER STUDIO

AULINE SHINDLER STUDIO

SHINDLER STUDIO

MARIAN CHASE STUDIO

KITCHEN COOK

KITCHEN EAT

STAIR

MARIAN CHASE STUDIO

CLYDE CHASE STUDIOP

AULINE SHINDLER STUDIO

SHINDLER STUDIO

Guest

MARIAN CHASE STUDIO

Quantity: 2

ENTRANCE

ARRIVAL

MORNING

KITCHEN EAT

ENTRANCE

CLYDE CHASE STUDIO

PAULINE SHINDLER STUDIO

EVENING

SHINDLER STUDIO

09_Schindler House_by Schindler

MARIAN CHASE STUDIO

LEAVING

COURTYARD

GUEST BED

ENTRANCE

GARAGE

ENTRANCE

GARAGE

144

145

7 8

9 3 2

13 16

7 8

9 3 2

14 13 16

1 Garage 2 Guest Bedroom 3 Guest closet 4 Guest Bathroom 5 Kitchen 6 Chase Entry 7 Bathroom 8 Clyde Chase Srudio 9 Chase Nursery 10 Marian Chase Studio 11 Pauline Schindler Studio 12 Courtyard 13 Schindler Studio 14 Schindler Entry 15 Stair 16 Schindler Studio Bath

09_Schindler House_by Schindler

17 Patio

146

147

7 8

9 3 2

13 16

7 8

9 3 2

13 16

09_Schindler House_by Schindler

17 Patio

148

149

7 8

9 3 2

13 16

9 3 2

13 16

09_Schindler House_by Schindler

17 Patio

150

151

Room Weights

Room Area & Ratio 9 Original Area Ratio Schindler Studio 1 0.97 Schindler Studio 2 3.41 Schindler Studio 3 24.99 Marian Chase Studio 36.52 0.38 Clyde Chase Studio 1 3.30 Clyde Chase Studio 2 31.61 Clyde Chase Studio 3 2.94 Pauline Schindler Studio 39.39

Low Resolution Area Ratio 1.24 3.38 27.74 21.78 0.36 3.30 31.93 2.94 55.65

Mid Resolution High Resolution Area Ratio Area Ratio 3.63 1.07 3.47 3.40 25.40 32.52 36.33 33.15 0.39 0.39 3.41 3.97 34.74 33.63 2.64 3.18 40.27 46.31

Bathroom Chase Nursery Kitchen 1 Kitchen 2 Guest Bedroom 1 Guest Bedroom 2 Guest Bathroom Schl Studio Bath 1 Schl Studio Bath 2

7.30 7.00 1.60 16.99 2.14 25.90 6.52 0.87 6.40

7.17 9.14 5.14 27.11 2.19 24.29 5.99 7.45 7.45

5.99

Patio Guest Closet Chase Entry Garage Courtyard 1 Courtyard 2 Stair Schindler Entry 1 Schindler Entry 2

8.48 5.96 13.18 28.18 3.72 81.85 1.61 4.12 5.85

TOTAL

369.99

09_Schindler House_by Schindler

0.20

0.41

9.82 5.57 13.51 29.70 3.28 82.89 2.00 4.10 4.80 399.36

6.71

7.54 7.10 1.29 16.99 6.55 25.18 6.44 5.15 5.15

8.63

8.47

8.10

3.23 3.70 8.25

5.96 13.26 28.18 3.73 81.95 1.60 4.11 4.91

398.80

383.96

6.81 1.83

0.24

19.45 2.14

0.19

21.34 6.15 6.71

14.96

0.38

29.31 3.73 84.32

0.41

0.21

0.39

152

153

10_The Farnsworth House_by Mies Agent Simulation Application Analysis Evaluation

154

Introduction

Photos/Original Plans

Introduction The Edith Farnsworth House, formerly the Farnsworth House,[6] is a historical house designed and constructed by Ludwig Mies van der Rohe between 1945 and 1951. The house was constructed as a one-room weekend retreat in a rural setting in Plano, Illinois, southwest of Chicago’s downtown. The steel and glass house was commissioned by Edith Farnsworth. Van der Rohe created a 1,500-square-foot (140 m2) structure that is widely recognized as an exemplar of International Style of architecture. 155

10_The Farnsworth House_by Mies

Agent Simulation

Agent Behaviour Outline A total of 2 master agents a 2 guests agents. The master agents behaviour is that of a normal day, including work, cooking and dining followed by time spent in the living space. Guests are entertained occasionally.

10 Seek Entry Terrace Dining Room Living Room Kitchen Guest Bedroom Guest Bathroom Bathroom Office Bedroom Mechanical

Wait X

✓ ✓ ✓ X X

✓ ✓ ✓ ✓

X 15-60 15-60 X X X 3-15 30-120 360-480 X

10_The Farnsworth House_by Mies

Master Waypoints WanderTime X X 2 5-10 3 15-60 5 5-10 X X X X 2 1-5 X X 3 2-5

Seek

✓ ✓ X X

✓ ✓ X X X

✓

Guest Wait Waypoints WanderTime Seek 1-2 X X 15-60 2 5-10 X X X X X X 360-480 3 2-5 3-15 2 1-5 X X X X X X X X X X

Wait

Staff Waypoints

WanderTime

156

157

Master

Quantity: 2

ENTRANCE

MORNING

BATHROOM

KITCHEN

DINING

EVENING

LUNCH

BATHROOM

OFFICE

KITCHEN

DINING

BATHROOM

OFFICE

KITCHEN

DINING

LIVING

Guest

BEDROOM

OFFICE

Quantity: 2

ENTRANCE

MORNING

ARRIVAL

ENTRANCE

DINING

LUNCH

GUEST BATH

DINING

GUEST BED

EVENING

GUEST BATH

DINING

GUEST BATH

LEAVING

ENTRANCE

10_The Farnsworth House_by Mies

LEAVING

ENTRANCE

158

159

3 2 7

9 4

3 2 7

9 4

1 Patio 2 Dining Area 3 Kitchen 4 Bedroom 5 Living Area 6 Office 7 Guest Bath 8 Mech 9 Bathroom

10_The Farnsworth House_by Mies

160

161

3 2 7

9 4

1 Patio 2 Dining Area 3 Kitchen 4 Bedroom 5 Living Area 6 Office 7 Guest Bath 8 Mech 9 Bathroom

10_The Farnsworth House_by Mies

162

163

3 2 7

9 4

3 2 7

9 4

1 Patio 2 Dining Area 3 Kitchen 4 Bedroom 5 Living Area 6 Office 7 Guest Bath 8 Mech 9 Bathroom

10_The Farnsworth House_by Mies

164

165

Room Weights

Room Area & Ratio 10 Area

Original Ratio

Living Area Office

30.33 22.57

Kitchen Dining Bathroom

15.28 25.01 6.08

Bedroom Guest Bathroom Mechanical Patio

33.27 6.07 6.15 59.58

Total

204.39

10_The Farnsworth House_by Mies

Low Resolution Mid Resolution High Resolution Area Ratio Area Ratio Area Ratio

0.25

31.43 23.93

0.23

0.28

0.22

23.08 35.59 6.08

0.47

0.51

39.09 6.03 6.15 59.58 230.96

0.34

28.05 44.69

0.32

0.16

12.97 24.92 5.89

0.19

0.48

0.47

59.58

34.01 6.57 6.46 59.58

232.79

224.22

36.74 43.60 13.45 21.85 4.03 43.43 6.02

4.07

166

167

11_Kaufmann House_by Neutra Agent Simulation Application Analysis Evaluation

168

Introduction

Photos/Original Plans

Introduction The Kaufmann Desert House, or simply the Kaufmann House, is a house located in Palm Springs, California, that was designed by architect Richard Neutra in 1946. Completed between 1946-1947, the Kaufmann House was a vacation home for Edgar J. Kaufmann Sr. and his family to escape the harsh winters of the northeast. The design of the house is quite simplistic; at the center of the house is the living room and the dining room that is the heart of the house and the family activity. The rest of the house branches out like a pinwheel in each of the cardinal directions. 169

11_Kaufmann House_by Neutra

Agent Simulation

Agent Behaviour Outline A total of 3 masters, 2 staff, and 2 guests. The master agents undertake daily activities typical of a resident. Guests are present occasionally for events and dining. A staff agent sporadically cleans and prepares food for the master agent/guest.

11 Seek Entry Living Room Dining room Kitchen Pantry Master Bathroom Master Bedroom Master Dressing Room Staff Bathroom Staff Bedroom Guest Bathroom Guest Bedroom Gallery Patio Storage Utility Car Shelter Leave Car Shelter Back

Wait X

✓ ✓ X X

✓ ✓ ✓ X X X X

✓ ✓ ✓ X

✓ X

X X 15-60 X X X 360-480 X X X X X X 15-60 X X 1-3 X

11_Kaufmann House_by Neutra

Master Waypoints WanderTime X X 3 15-60 X X X X X X 3 5-30 X X 4 1-15 X X X X X X X X 3 1-3 5 1-15 3 1-2 X X X X X X

Seek

✓ ✓ ✓ X X X X X X X

✓ ✓ ✓ ✓ X X

✓ ✓

Guest Wait Waypoints WanderTime Seek 1-3 X X X X 3 15-60 X 15-60 X X ✓ X X X ✓ X X X ✓ X X X X X X X X X X X X X X X ✓ X X X ✓ X 3 5-15 X 360-480 X X X X 3 1-3 X 15-60 5 1-15 ✓ X X X X X X X ✓ 1-3 X X X 1-3 X X X

Wait X X X X X X X X X 360-480 X X X X X X X X

Staff Waypoints WanderTime X X X X 5 1-3 5 1-10 3 1-2 X X X X X X 3 5-15 X X X X X X X X 5 1-3 X X 3 1-2 X X X X Cleaning Staff 5 1-3

170

171

Master

Quantity: 3

ENTRANCE

MORNING

MASTER BATHROOM

MASTER DRESSING

PATIO

EVENING

LUNCH

CAR SHELTER LEAVE

CAR SHELTER BACK

LIVING ROOM

CAR SHELTER LEAVE

PATIO

DINING ROOM

CAR SHELTER BACK

DINING ROOM

PATIO

GALLERY

MASTER BATHROOM

MASTER DRESSINGM

LIVING ROOM

DINING ROOM

STORAGE

ASTER BEDROOM

Staff

Quantity: 2

ENTRANCE

STAFF CLEANING

UTILITYU

MORNING

TILITY

UTILITY

STAFF CLEANING

UTILITY

EVENING

LUNCH KITCHENP

ANTRYP

STAFF PATIO

KITCHENP

ANTRYP

STAFF DINING ROOM

STAFF PATIO

KITCHEN

ANTRY

STAFF DINING ROOM

STAFF PATIO

KITCHEN

KITCHENP

STAFF DINING ROOM

ANTRY

ANTRYP

STAFF PATIO

KITCHEN

PANTRY

STAFF DINING ROOM

KITCHEN

PANTRY

ANTRY

STAFF PATIO

Guest

STAFF DINING ROOM

KITCHEN

PANTRY

Quantity: 2

ENTRANCE

LEAVING

ARRIVAL

ENTRANCE

CAR SHELTER BACKP

ATIO

DINING ROOM

GALLERY

GUEST BATHROOM

11_Kaufmann House_by Neutra

LIVING ROOM

PATIO

GUEST BATHROOM

DINING ROOM

GUEST BEDROOM

ENTRANCE

CAR SHELTER BACK

172

173

9 3

6 15 2

7 8

9 3

6 15 2

7 8

1 Staff Bedroom 2 Staff Bedroom 3 Bath room 4 Pantry 5 Kitchen 6 Patio 7 Entry 8 Car shelter 9 Guest Bedroom 10 Dining Room 11 Living Room 12 Gallery 13 Storage 14 Master Bedroom 15 Master Dressing Room 16 Utility

11_Kaufmann House_by Neutra

174

175

9 3

6 15 2

7 8

9 3

6 15 2

7 8

11_Kaufmann House_by Neutra

176

177

9 3

6 15 2

7 8

9 3

6 15 2

7 8

11_Kaufmann House_by Neutra

178

179

Room Weights

Room Area & Ratio 11

11_Kaufmann House_by Neutra

Original Area Ratio 37.37 19.40 52.97 1.79 20.31 20.65 6.94 8.98 9.51 0.62 59.72 0.72 7.17 1.38 13.14 7.31 29.58 38.55

Low Resolution Area Ratio 36.63 18.63 50.88 1.78 21.02 11.44 6.94 8.38 9.46 0.61 58.56 0.56 7.13 1.44 13.14 7.31 31.37 39.12

Mid Resolution Area Ratio

Entry A Entry B Living Room Living Room Bar Dining Room Kitchen Kitchen Fridge Pantry Gallery Patio Storage A Storage B Storage Wardrobe Utility A Utility B Corridor Car Shelter Master Bathroom Master Bathroom Shower Guest Bathroom A Guest Bathroom B Guest Bathroom Shower Staff Bathroom Staff Bathroom Shower Master Dressing Rm A Master Dressing Rm B Master Dressing Rm C Master Dressing Rm D Master Dressing Rm E

6.68 1.01 4.82 4.46 0.56 6.06 2.04 5.32 1.69 2.17 1.70 5.73

6.73 1.01 4.78 4.27 0.56 6.05 2.30 5.32 1.69 2.17 1.70 5.73

6.63

Master Bedroom A Master Bedroom B Master Bedroom C Master Bedroom Dresser Master Bedroom Bar Staff Bedroom A Staff Bedroom B Staff Bedroom Wardrobe A Staff Bedroom Wardrobe B Staff Bedroom Balcony Guest Bedroom A Guest Bedroom B Guest Bedroom C Guest Bedroom Wardrobe A Guest Bedroom Wardrobe B Guest Bedroom Balcony A Guest Bedroom Balcony B

4.32 0.86 26.85 2.01 0.78 15.68 17.33 2.26 1.35 9.02 19.54 12.10 19.34 3.34 1.16 11.95 11.86

Total

536.58

0.07

0.29

4.32 0.86 26.04 2.01 0.78 16.45 17.35 1.87 1.35 9.77 18.25 12.09 19.34 3.06 1.16 11.78 11.78 525.34

47.78 21.86 53.78 0.90 15.76 35.28 1.43 9.03 7.24

0.63

60.61 0.71 5.31 1.19 13.26 7.56 29.96 33.24

6.60 1.01 4.81

1.06 4.98

4.54 1.12

4.46 0.97

0.08

6.09 0.97

0.09

5.34

1.69 2.06 1.69 5.73

0.31

4.22 0.72 26.04 1.82 0.62 15.68 17.33 2.25 1.71 13.69 2.02 11.92 19.75 1.40 1.15 12.86 12.97 531.59

High Resolution Area Ratio 36.84 19.46 51.97 1.84 20.55 20.74 0.83 9.12 6.85 0.62 52.17 0.88 7.29 1.38 13.13 7.30 31.47 27.61

6.08 1.00 5.31 1.69 1.08 1.69

0.08

5.73

0.30

5.68 0.75 26.04 1.46 0.63 15.68 17.33 2.26 1.71 20.53 1.92 11.94 19.33 0.32 1.15 8.98 8.91

0.29

494.95

180

181

12_Miller House_by Saarinen Agent Simulation Application Analysis Evaluation

182

Introduction

Photos/Original Plans

Introduction

The Miller House and Garden, also known as Miller House, is a mid-century modern home designed by Eero Saarinen and located in Columbus, Indiana, United States.[3] The residence was commissioned by American industrialist, philanthropist, and architecture patron J. Irwin Miller and his wife Xenia Simons Miller in 1953. The Miller house was meant to be a year-round residence, rather than just a vacation home.The Millers wanted a home in which they could entertain heads of state and titans of industry. The Miller House epitomizes the modernist architectural tradition developed by Ludwig Mies van der Rohe with its open and flowing layout, flat roof, and stone and glass walls. 183

12_Miller House_by Saarinen

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline A total of 5 master agents which include parents and children undertake daily activities typical of a resident. Guests are entertained occasionally. A staff agent, behaving as a live-in nanny, prepares food, cleans, and entertains the children. 12 Seek Entry Carport TV Lounge Child Area Child Bedroom Child Storage Child Lounge Fireplace Guest Bedroom Guest Bathroom Nanny Bedroom Nanny Bathroom Kitchen Kitchen Pantry Master Bedroom Master Brunch Patio Dining room Living Room Stair

Wait X X

✓ ✓ ✓ ✓ ✓ ✓ X X X X X X

✓ ✓ ✓ ✓ X

12_Miller House_by Saarinen

X X X X 360-480 X X X X X X X X X 360-480 15-30 15-60 X X

Master Waypoints WanderTime X X X X 3 15-60 10 5-10 3 2-5 3 1-2 3 15-60 2 5-30 X X X X X X X X X X X X 3 2-5 X X X 3 X

X 15-60 X

Seek

✓ ✓ ✓ X X X X

✓ ✓ ✓ X X X X X X

✓ ✓ X

Guest Wait Waypoints WanderTime Seek 1-3 X X X X 3 1-2 X X 3 15-60 X X X X ✓ X X X X X X X X X X X X X 2 5-30 X 360-480 3 2-5 X 3-15 2 1-5 X X X X ✓ X X X ✓ X X X ✓ X X X ✓ X X X X X X X X 15-60 1-3 X

X X X

✓ X X

Wait X X X X X X X X X X 360-480 3-15 X X X X X X X

Staff Waypoints WanderTime X X X X X X 5 1-10 X X X X X X X X X X X X 3 2-5 2 1-5 5 5-10 3 1-2 X X X X 6 X X Cleaning Staff 5

1-2 X X 1-3

184

185

Master

Quantity: 5

ENTRANCE LUNCH

MORNING

DINING ROOM

CHILD LOUNGE

CHILD STORAGE

EVENING

CHILD AREA

CHILD LOUNGE

TV LOUNGE

LIVING ROOM

CHILD STORAGE

CHILD LOUNGE

CHILD AREA

TV LOUNGE

FIRE PLACE

DINING ROOM

LIVING ROOM

CHILD STORAGE

CHILD AREA

FIRE PLACE

TV LOUNGE

LIVING ROOM

FIRE PLACE

CHILD

CHILDBED

Staff

ADULT

MASTER BED

MASTER BRUNCH

Quantity: 1

ENTRANCE STAFF CLEANING

MORNING

AFTERNOON

COOKING

KITCHEN PANTRY

KITCHEN

STAFF DINING

CHILD LOUNGE

STAFF CLEANING

KITCHEN PANTRY

KITCHEN

STAFF DINING

CHILD LOUNGE

NANNY BED

NANNY BATH

COOKING

CHILD AREA

EVENING

KITCHEN

STAFF DINING

CHILD LOUNGE

CHILD AREA

Guest

Quantity: 2

ENTRANCE

ARRIVAL

ENTRANCE

MORNING

CARPORT

TV LOUNGE

LIVING ROOM

DINING ROOM

FIRE PLACE

12_Miller House_by Saarinen

TV LOUNGE

EVENING

AFTERNOON

DINING ROOM

LIVING ROOM

FIRE PLACE

DINING ROOM

TV LOUNGE

LIVING ROOM

STAY

GUEST BEDG

UEST BATH

LEAVING

CARPOT

ENTRANCE

FIRE PLACE

186

187

13 14

5 6

18 24

19 28

27 26

13 14

5 6

18 24

19 27

28 29

20 23

1 Child Bedroom A 2 Child Bedroom B 3 Child Bedroom C 4 Child Area 5 Child Bathroom 6 Child Lounge 7 Child Storage 8 Living Room 9 Dining Room 10 TV Lounge 11 Fireplace 12 Master Bathroom 13 Master Bedroom 14 Master Bedroom Hall 15 Master Closet 16 Master Brunch

12_Miller House_by Saarinen

17 Pantry A 18 Kitchen 19 Living Bathroom 20 Pantry B 21 Pantry C 22 Staircase 23 Entry 24 Guest Bathroom 25 Guest closet 26 Guest Bedroom 27 Nanny Bedroom 28 Nanny Closet 29 Nanny Bedroom 30 Carport

188

189

13 14

5 6

18 24

19 28

27 26

13 14

5 6

18 24

19 27

28 29

20 23

12_Miller House_by Saarinen

18 22

17 Pantry A 18 Kitchen 19 Living Bathroom 20 Pantry B 21 Pantry C 22 Staircase 23 Entry 24 Guest Bathroom 25 Guest closet 26 Guest Bedroom 27 Nanny Bedroom 28 Nanny Closet 29 Nanny Bedroom 30 Carport

190

191

13 14

5 6

18 24

19 28

27 26

13 14

5 6

18 24

19 27

28 29

20 23

12_Miller House_by Saarinen

18 22

17 Pantry A 18 Kitchen 19 Living Bathroom 20 Pantry B 21 Pantry C 22 Staircase 23 Entry 24 Guest Bathroom 25 Guest closet 26 Guest Bedroom 27 Nanny Bedroom 28 Nanny Closet 29 Nanny Bedroom 30 Carport

192

193

Room Weights

Room Area & Ratio 12

12_Miller House_by Saarinen

Living Room Dining Room TV Lounge Kitchen A Kitchen B1 Kitchen B2 Chid Area Child Lounge

Original Area Ratio 97.69 53.65 38.61 17.88 0.41 4.71 43.46 28.96 20.36

Low Resolution Mid Resolution High Resolution Area Ratio Area Ratio Area Ratio 98.53 100.26 95.42 52.91 54.50 52.23 30.60 38.74 38.48 13.12 19.61 24.29 0.39 0.43 0.42 4.70 4.55 5.05 43.45 45.80 37.19 27.85 22.87 30.31 20.61 20.35 18.67

Master Bedroom 1 Master Bedroom 2 Master Bedroom 3 Master Bedroom 4 Guest Bedroom Child Bedroom A Child Bedroom B Child Bedroom C Nanny Bedroom Fireplace Child Storage

4.68 4.30 4.67 31.43 18.49 12.86 11.43 11.84 11.98 42.48 6.59

10.05 9.26 13.62 53.39 17.97 12.06 11.43 11.83 12.02 41.56 6.59

Master Bathroom Guest Bathroom Living Bathroom 1 Living Bathroom 2 Living Bathroom 3 Nanny Bathroom 1 Nanny Bathroom 2 Child Bathroom Al Child Bathroom A2 Child Bathroom AS Child Bathroom B1 Nanny Closet Entrance 1 Entrance 2 Staircase Patio Carport 1 Carport 2 Carport 3 Carport 4 Pantry A Pantry B Pantry C Guest Closet Master Closet A Master Closet B Master Closet Cl Master Closet C2 Master Bedroom Hall Master Brunch Master Storage 1 Master Storage 2

12.49 6.72 8.60 1.12 2.05 2.81 3.50 11.24 1.08 0.85 4.76 4.63 13.66 9.30 6.34 20.85 2.23 2.23 4.49 64.50 6.63 5.01 6.20 2.51 11.60 6.37 6.47 2.75 10.95 9.47 0.71 1.14

Total

734.13

0.21

0.36

13.77 6.72 8.48 1.06 2.05 2.81 3.50 11.23 1.08 0.85 4.75 4.42 13.10 9.69 5.38 20.94 2.23 2.23 20.14 64.50 6.64 4.94 6.34 2.42 11.51 4.51 5.33 3.15 13.23 7.71 0.26 1.13 771.87

0.50

0.24 0.48 29.53 20.36

0.26

12.54

0.21

14.19 12.24 11.81 42.55 6.59 12.41

12.40

6.72

6.72 8.59

9.04

1.11 3.50

3.50 11.65 1.05 0.79 5.74 4.71 11.71 9.32 0.96 23.53 2.28 2.28 4.59 65.01 6.56 1.54 6.04 2.50 12.67 6.22 6.46 2.74 10.21 9.47 0.71 1.14 698.81

0.20

1.11 2.04 3.96 3.03 11.88 1.08

2.04

0.34

2.19 1.06 2.07 31.45 18.49 10.10 11.27 11.76 11.69 40.76 6.29

0.35

0.69 4.63 4.84 13.66 9.30 6.34 20.60 2.23 2.23 4.48 64.29 6.26 5.01 2.50 2.50 11.25 6.59 6.49 2.82 11.81 9.47 0.70 2.07

0.36

706.33

194

195

13_Bailey House_by Koenig Agent Simulation Application Analysis Evaluation

196

Introduction

Photos/Original Plans

Introduction

The Bailey House, or Case Study House #21, is a steel-framed modernist house in the Hollywood Hills, designed by Pierre Koenig. The main house is a 30 by 44 feet (9.1 m × 13.4 m) rectangular plan with a solid rectangular core housing the utilities – two full bathrooms and a mechanical room. Beyond this core lay two efficiently arranged bedrooms. The threshold through this interior courtyard/core provides increased privacy (visually and acoustically) for the bedrooms. CSH #21 is arranged along a north-south axis with a carport on the Northside and a fully glazed Southside to take advantage of the best view and maximum sunlight for the winter months. 197

13_Bailey House_by Koenig

Agent Simulation

Agent Behaviour Outline A total of 2 master agents inhabit the property, undetaking daily activies typical of residents. Guests are invited occasionally for events and will ocassionally spend the night in the guest room.

13 Seek Entry Garage Living room Kitchen Dining room Master Bedroom Master Bathroom Guest Bathroom Guest Bedroom Library Terrace Garden

Wait X

✓ ✓ ✓ ✓ ✓ ✓ X X

✓ ✓ ✓

13_Bailey House_by Koenig

X X X X 15-60 360-480 15-30 X X X X X

Master Waypoints WanderTime X X 3 1-2 3 15-60 5 5-10 X X 3 2-5 X X X X X X 3 15-60 3 1-5 3 1-5

Seek

✓ X

✓ X X

✓ ✓ ✓ ✓ ✓

Guest Wait Waypoints WanderTime Seek 1-3 X X X X X X 3 15-60 X X X 15-60 X X X X X X X X 360-480 3 2-5 3-15 2 1-5 X 3 15-60 X 3 1-5 X 3 1-5

Wait

Staff Waypoints

WanderTime

198

199

Master

Quantity: 2

ENTRANCE

MORNING

LUNCH

MASTER BATHM

GARAGE

GARDEN

TERRACE

LIVING

LIBRARY

EVENING

ASTER BATH

KITCHEN

DINING

KITCHEND

INING

MASTER BED

LIVING

LIBRARY

TERRACE

GARDEN

GARAGE

LIVING

LIBRARY

TERRACE

GARDEN

TERRACE

GARAGE

GARDEN

LIVING

MASTER BATH

LIBRARY

LIVING

GARAGE

LIBRARY

Guest

Quantity: 2

ENTRANCE

ARRIVAL

EVENING

AFTERNOON

MORNING

ENTRANCE

LIVING

LIBRARY

TERRACE

GARDEN

LIVING

13_Bailey House_by Koenig

DINING

LIBRARY

TERRACEG

ARDEN

GUEST BATH

GUEST BED

ENTRANCE

DINING

200

201

2 9

4 5

15 12

18 19

2 9

4 5

19 26

13_Bailey House_by Koenig

202

203

2 9

4 5

15 12

18 19

7 8 1 3

4 5

18 19

1 Enterance 2 Terrace A 3 Garage 4 Garden F 5 Garden E 6 Terrace F 7 Garden B 8 Dining Room 9 Kitchen 10 Dining Room 11 Library A 12 Library B 13 Bathroom A 14 Washroom 15 Bathroom B 16 Corridor

13_Bailey House_by Koenig

17 Bedroom A 18 Closet A 19 Closet B 20 Bedroom B 21 Terrace B 22 Terrace C 23 Terrace D 24 Garden C 25 Terrace E 26 Garden D

204

205

2 9

15 12

18 19

2 9

18 19

1 Enterance 2 Terrace A 3 Garage 4 Garden F 5 Garden E 6 Terrace F 7 Garden B 8 Dining Room 9 Kitchen 10 Dining Room 11 Library A 12 Library B 13 Bathroom A 14 Washroom 15 Bathroom B 16 Corridor

13_Bailey House_by Koenig

17 Bedroom A 18 Closet A 19 Closet B 20 Bedroom B 21 Terrace B 22 Terrace C 23 Terrace D 24 Garden C 25 Terrace E 26 Garden D

206

207

Room Weights

Room Area & Ratio 13

Living Room Dining Room Kitchen

Original Area Ratio 28.41 12.38 0.19 15.47

Low Resolution Mid Resolution Area Ratio Area Ratio 27.15 26.76 7.19 0.19 15.77 0.19 22.86 13.73

High Resolution Area Ratio 28.46 12.38 0.19 15.58

Bathroom A Bathroom B Washroom Bedroom A Bedroom B Closet A Closet B Library A Library B

3.64 3.64 6.52 13.53 13.65 0.00 0.00 2.59 2.68

0.16

3.74 3.16 7.25 13.87 15.30 0.20 0.20 2.94 2.94

0.19

2.99 3.63 6.30 14.37 15.13 2.84 2.70 3.22 2.55

0.16

Garage A Garage B Garden A Garden B Garden C Garden D Garden E Garden F Garden G Terrace A Terrace B Terrace C Terrace D Terrace E Terrace F Corridor A Corridor B Corridor C Entrance

1.72 36.67 8.43 15.28 4.85 17.95 5.08 12.74 5.34 5.34 4.94 9.69 9.62 4.84 9.37 7.37 4.10 3.97 14.08

0.63

1.77 37.37 8.43 15.27 4.85 17.95 5.07 12.74 5.34 5.34 4.94 9.68 9.62 4.83 9.37 6.73 5.42 4.28 14.66

0.60

2.41 38.31 8.73 15.27 4.85 17.95 5.07 12.70 5.34 5.34 4.94 9.68 9.62 4.83 9.37 7.55 4.10 4.55 16.10

0.63

Total

283.89

13_Bailey House_by Koenig

293.79

0.16

3.37 3.81 5.96 14.02 13.39 2.71 3.26 8.58 2.67

0.63

1.83 36.77 8.43 15.27 4.85 17.95 5.07 12.74 5.34 5.34 4.94 9.68 9.62 4.83 9.37 7.58 2.67 8.63 6.03 291.47

296.90

208

209

14_Rosen House_by Ellwood Agent Simulation Application Analysis Evaluation

210

Introduction

Photos/Original Plans

Introduction Rosen House, Los Angeles, was built by architect Craig Ellwood in 1961-63. Craig Ellwood was one of the architects who took part in the Case Study Houses program in the 1950s, designed to promote modern architecture and the use of new industrial materials in domestic architecture. 211

14_Rosen House_by Ellwood

Agent Simulation

Plan Diagram of Agent Simulation

Agent Behaviour Outline A total of 4 master agents, two of which are children. The master agents undetake daily acitvities typicaly of a residence. Guest are frequent and their behaviours include attending events and staying the night in the guest room.

14 Seek Entry Carport Storage Swimming Pool Deck Kitchen Dining room Living Room Fireplace Guest Living Guest Bed Guest Bathroom Child Bathroom Child Bedroom Office Office Bathroom Courtyard Master Bedroom Master Bathroom

Wait X X X

✓ ✓ ✓ ✓ ✓ ✓ X X X

✓ ✓ ✓ ✓ ✓ ✓ ✓

14_Rosen House_by Ellwood

X X X X X X 15-60 X X X X X 3-15 360-480 30-120 3-15 X 360-480 15-30

Master Waypoints WanderTime X X X X X X 3 5-10 5 1-10 5 5-10 X X 3 15-60 2 5-30 X X X X X X 2 1-5 3 2-5 X X 2 1-5 5 1-10 3 2-5 X X

Seek

✓ ✓ X

✓ ✓ ✓ ✓ ✓ ✓ X X X X X X X

Guest Wait Waypoints WanderTime Seek 1-3 X X X 3 1-2 X X X X 3 5-10 X 5 1-10 X X X 15-60 X X 1-3 X X X 2 5-30 X 3 15-60 360-480 3 2-5 3-15 2 1-5 X X X X X X X X X X X X X X X X X X X X X

Wait

Staff Waypoints

WanderTime

212

213

Master

Quantity: 4

ENTRANCE

MORNING

LIVING

COOKING&EAT

KITCHEN

DINING

CARPORT

CHILD BATH

OFFICE BATHM

STORAGE

OFFICE

FIRE PLACE

COURTYARD

LIVING

LUNCH

LIBRARY

CHILD BATH

ASTER BATH

KITCHEN

OFFICE BATH

OFFICE

STORAGE

CARPORT

EVENING

COURTYARD

DINING

MASTER BATH COOKING&EAT

KITCHEND

INING

LIVING

CHILD BATH

OFFICE BATH

CHILD

GUEST BED

FIRE PLACE

MASTER BATH

ADULT

GUEST BATHE

NTRANCE

Guest

CARPOT

Quantity: 2

ENTRANCE

ARRIVAL

GUEST BATH

MORNING

EVENING

AFTERNOON

LIVING

DINING

DINING DINING ENTRANCE

GUEST LIVING LIVING

LIVING

ENTRANCE

SWIMING OFFICE

GUEST LIVING

FIRE PLACE

DECK OFFICE

GUEST LIVING

CHILD

GUEST BED

14_Rosen House_by Ellwood

GUEST BATH

ADULT

ENTRANCE

CARPOT

214

215

24 25 26

22 27

28 29

1 Swimming Pool 2 Pool Deck 3 Carport Storage 4 Carport 5 North Deck 6 South Deck 7 Guest Bedroom A 8 Guest Bathroom A 9 Guest closet A 10 Guest Living Room 11 Dining Room 12 Kitchen 13 Guest Bedroom B 14 Guest Bathroom B 15 Child Bedroom A 16 Child Bedroom B

14_Rosen House_by Ellwood

17 Child Bathroom A 18 Child Bathroom B 19 Courtyard 20 Dining Room 21 Entry 22 Dining room Bar 23 Master Bedroom 24 Closet A 25 Master Bathroom 26 Closet B 27 Living Room 28 Office Bathroom 29 Office

216

217

24 25 26

13 14

22 27

28 29

14_Rosen House_by Ellwood

218

219

24 25 26

22 27

28 29

14_Rosen House_by Ellwood

220

221

Room Weights

Room Area & Ratio 14 Original Ratio

Living Room Dining Room A Dining Room B Guest Living Office Kitchen A Kitchen B

Area 44.78 19.90 42.12 28.36 20.85 1.40 9.95

Master Bedroom Master Bathroom A Master Bathroom B Master Bathroom C Guest Bedroom A Guest Bathroom AA Guest Bathroom AB Guest Bathroom AC Guest Bathroom AD Guest Bathroom AE Guest Bedroom B Guest Bathroom B Child Bedroom A Child Bedroom B Child Bathroom A Child Bathroom B Office Bathroom A Office Bathroom B Office Bathroom C Office Bathroom D Dining Room Bar

23.90 0.60 0.60 20.00 28.08 14.40 4.60 7.20 1.30 14.40 11.90 4.50 15.90 15.90 8.10 8.10 3.00 3.00 1.50 7.50 1.40

Carport Carport Storage A Carport Storage B Carport Storage C Entry Swimming Pool Pool Deck North Deck A North Deck B South Deck Master Closet A Master Closet B Guest A Closet A Guest A Closet B Guest B Closet Child Closet A Child Closet B Storage A Storage B Storage C Storage D Storage E Courtyard Fireplace

16.02 8.28 5.52 2.76 13.92 57.59 167.98 49.20 30.74 49.20 7.40 6.20 3.20 0.80 1.50 5.10 5.10 3.30 1.36 6.21 0.58 0.82 64.80 1.40

Total

14_Rosen House_by Ellwood

823.00

0.20

0.23

Low Resolution Area Ratio 49.66 15.13 19.76 33.38 0.18 22.38 1.65 8.60

Mid Resolution High Resolution Area Ratio Area Ratio 56.67 40.56 20.62 18.47 43.23 44.15 0.18 29.01 0.17 31.48 1.44 21.27 1.39 1.33 9.95 8.66

31.63 0.55 0.10 13.54 28.08 18.02 6.69 6.15 3.33 18.02 11.69 4.41 16.34 15.45

23.90 0.59 0.60

21.59 28.08 14.72 4.60 7.45 1.67 14.72

0.24

7.95 8.22 2.29 2.29 1.47 6.47 0.62

0.55

10.85 8.65 6.31 2.33 14.33 57.58 167.97 49.20 30.73 66.53 2.42 10.26 3.23 0.79 1.60 5.37 4.91 11.37 1.12 6.33 0.38 1.67 59.71 0.90 829.80

11.80 45.17

0.25

15.90 15.90 8.09 0.84

3.00 1.00 6.17 2.10

1.17 5.15

1.54

41.28 14.33

16.02 8.64 5.76 2.88 12.25 57.58 167.97 49.20

0.57

911.63

0.21

7.72 2.64

8.09

3.01

30.73 52.58 1.19 2.79 16.82 1.58 0.52 5.09 5.09 1.28 0.54 0.21 0.31 0.53 69.77 1.40

24.07 0.73 0.59 19.00 27.47 14.76 4.67 7.33 1.01 14.86 11.59 4.77 15.28 16.92 8.04

0.56

9.04 5.28 21.11 57.58 167.97 28.60 30.73 91.57 7.00 5.87 1.62 1.23 0.88 5.05 5.11 2.01 0.77 0.51 0.36 9.98 35.36 1.07

0.60

897.62

222

223

15_White U House_by Ito Agent Simulation Application Analysis Evaluation

224

Introduction

Photos/Original Plans

Introduction White U was designed for Toyo Ito’s older sister, who had just lost her husband to cancer. The internal layout of the building consists of the long curved corridor, which terminates at each end in bedrooms: at one end the mother’s, at the other the daughters’. These ends of the corridor are dark, with the primary light source being the entrance to the internal courtyard, near the center of the bend - at the symbolic meeting point of the family. The surfaces inside are all white, making a minimalist space for contemplative thought. 225

Agent Simulation

Agent Behaviour Outline The master agent here includes mother and child. The agents undertake daily activities, which include dining, specifically for this project, spending time in the gardens and other day to day activities. Guests agents are occasionally present for dining.

15 Seek Entrance Main room Study Storage WC Bedroom A Main Room Dining Kitchen Bathroom Pantry Garden Front Garden Courtyard Bedroom B

15_White U House_by Ito

Wait X

✓ ✓ X

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ X

X X X X X 360-480 X X X X X X X X

Master Waypoints WanderTime X X 3 15-60 3 15-60 X X 2 1-5 3 2-5 3 15-60 3 5-30 3 5-10 3 1-5 3 15-30 3 15-30 3 5-10 X X

Seek

✓ ✓ ✓ X

✓ X

✓ X X X

✓ ✓ X

✓

Guest Wait Waypoints WanderTime Seek 1-3 X X X 3 15-60 X 3 15-60 X X X X 2 1-5 X X X X 3 15-60 X X X X X X X X X X 3 15-30 X 3 15-30 X X X 360-480 X X

Wait

Staff Waypoints

WanderTime

226

227

Master

Quantity: 2

ENTRANCE

MORNING

COURTYARD

BATHROOM

EVENING

LUNCH

PANTRY

MAIN ROOM B

KITCHEN

MAIN ROOM B

GARDEN

ENTRANCE

KITCHEN

PANTRY

MAIN ROOM B

Guest

STUDY

BATHROOM

BEDROOM

Quantity: 2

ENTRANCE

ARRIVAL

LIVING

BEDROOM

ENTRANCE

GARDEN

ENTRANCE

MAIN ROOM A

15_White U House_by Ito

FRONT GARDEN

STUDY

MAIN ROOM B (DINING)

GARDEN

MAIN ROOM B (DINING)

228

229

2 10

1 Front Garden 2 Main Room 3 Kitchen 4 Pantry 5 Bathroom 6 Courtyard 7 Study 8 Garden 9 Enterance 10 Storage 11 WC 12 Bedroom

15_White U House_by Ito

230

231

2 10

1 Front Garden 2 Main Room 3 Kitchen 4 Pantry 5 Bathroom 6 Courtyard 7 Study 8 Garden 9 Enterance 10 Storage 11 WC 12 Bedroom

15_White U House_by Ito

232

233

2 10

1 Front Garden 2 Main Room 3 Kitchen 4 Pantry 5 Bathroom 6 Courtyard 7 Study 8 Garden 9 Enterance 10 Storage 11 WC 12 Bedroom

15_White U House_by Ito

234

235

Room Weights

Room Area & Ratio

15 Original Ratio

Entrance MainRoom Al MainRoom A2 MainRoom B Storage Kitchen Pantry Garden A Garden B Front Garden Courtyard A Courtyard B

Area 11.41 9.49 12.15 16.23 5.34 8.78 3.66 44.95 15.14 3.17 1.96 62.11

Study Bathroom Toilet

15.80 2.17 3.42

0.08

Bedroom A Bedroom B

12.52 9.82

0.09

Total

236.47

15_White U House_by Ito

0.81

Low Resolution Area Ratio 11.25 8.55 17.52 18.11 5.39 3.50 0.81 4.69 44.34 15.05 3.17 0.71 62.03

Mid Resolution Area Ratio

21.88 3.20 3.41

18.43

0.08

12.52 8.83

0.09

246.44

10.85 9.51 11.99 3.88 5.11 7.83 6.19

0.73

44.33 15.04 3.16 1.82

69.60

22.98

0.17

15.80 8.51 3.45

0.10

0.08

11.87 8.87

0.07

3.41 12.82 8.81 255.35

High Resolution Area Ratio 11.32 35.89 16.44 6.00 5.44 5.91 0.82 3.82 44.33 15.04 3.16 1.81 76.07

273.82

236

237

16_Bridge House_by Ellwood Agent Simulation Application Analysis Evaluation

238

Introduction

Photos/Original Plans

Introduction Designed in 1968, but unbuilt. It is essentially a long rectangle enclosed in glass — almost nothing is added to the essentials of the flat floor and roof; the only interior walls and doors are those to the bathrooms and utility room. Everything else is designed for maximum openness, both to the outside world and the rest of the house 239

16_Bridge House_by Ellwood

Agent Simulation

Agent Behaviour Outline The house is presumed to be occupied by 2 master agent who behave as residents undertaking typical day to day activities. Guests are present occasioanlly, either vistiing or dining.

16 Seek Entry Porch Living Room Dining Room Bedroom Bathroom Storage Kitchen Guest Bedroom

Wait X

✓ ✓ ✓ ✓ ✓ ✓ ✓ X

16_Bridge House_by Ellwood

X 1-3 X 15-60 360-480 X X X X

Master Waypoints WanderTime X X X X 3 15-60 X X X X 3 5-10 3 1-2 3 5-30 X X

Seek

✓ X

✓ ✓ X

✓ X X

✓

Guest Wait Waypoints WanderTime Seek 1-3 X X X X X 1-3 X X 15-60 X X X X X X 3 5-10 X X X X X X 360-480 3 2-5

Wait

Staff Waypoints

WanderTime

240

241

Master

Quantity: 2

ENTRANCE

BATHROOM

MORNING

LIVING

DINING

KITCHEN

LIVING

LUNCH

PORCH

DINING

KITCHEN

STORAGE

LIVING

BATHROOM

KITCHEN

DINING

EVENING

BATHROOM

Guest

BEDROOM

Quantity: 2

ENTRANCE

ARRIVAL

BATHROOM

AFTERNOON

LIVING

DINING

16_Bridge House_by Ellwood

LIVING

DINING

STAYING

LIVING

EVENING

LIVING

DINING

BATHROOM

GUEST BED

ENTRANCE

242

243

4 2

7 8

1 Porch B 2 Entry 3 Dining 4 Kitchen 5 Bathroom A 6 Storage 7 Bathroom B 8 Bedroom B 9 Poarch A 10 Bedroom A 11 Living Room

16_Bridge House_by Ellwood

244

245

4 2

7 8

1 Porch B 2 Entry 3 Dining 4 Kitchen 5 Bathroom A 6 Storage 7 Bathroom B 8 Bedroom B 9 Poarch A 10 Bedroom A 11 Living Room

16_Bridge House_by Ellwood

246

247

4 2

7 8

1 Porch B 2 Entry 3 Dining 4 Kitchen 5 Bathroom A 6 Storage 7 Bathroom B 8 Bedroom B 9 Poarch A 10 Bedroom A 11 Living Room

16_Bridge House_by Ellwood

248

249

Room Weights

Room Area & Ratio

16 Original Ratio

Living Room A Living Room B Dining Kitchen

Area 2.55 74.83 10.20 13.99

Bathroom A Bedroom A

3.45 17.48

Bathroom B Bedroom B Storage Entry Porch A Porch B

3.45 34.62 2.40 28.94 57.10 57.10

Total

306.10

16_Bridge House_by Ellwood

Low Resolution Area Ratio 2.18 131.34 0.45 4.83 9.74

Mid Resolution High Resolution Area Ratio Area Ratio 0.78 7.11 117.94 69.80 0.39 0.43 30.63 36.87 17.05 15.14

0.06

4.67 23.20

3.36

0.59

0.01 16.30 2.58 19.92 57.10 57.10

0.33

329.33

0.08

0.06

3.39 24.70

0.07

0.53

0.48

57.09

1.08 34.25 2.21 34.55 57.09 57.09

326.27

382.52

17.83 3.01 26.86

0.46

2.70

29.45 57.09

250

251

17_Koshino House_by Ando Agent Simulation Application Analysis Evaluation

252

Introduction

Photos/Original Plans

Introduction

Tadao Ando’s design for the Koshino House features two parallel concrete rectangular confines. The forms are partially buried into the sloping ground of a national park and become a compositional addition to the landscape. The northern volume consists of a two-story height containing a double-height living room, a kitchen, and a dining room on the first floor with the master bedroom and a study on the second floor. The southern mass then consists of six linearly organized children’s bedrooms, a bathroom, and a lobby. Connecting the two spaces is a below-grade tunnel that lies beneath the exterior stairs of the courtyard. 253

Agent Simulation

Agent Behaviour Outline The ground floor has been considered, a total of 5 masters and 2 guests. The master agents consist of 2 parents and 3 children. The masters agents undertake generic daily behaviours. Guests agents are present occasionally, visting for socially and staying the night.

17 Seek Entry Garden Stair Kitchen Living Room Study Bathroom Bedroom Dining Tatami Room

Wait X

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

17_Koshino House_by Ando

X X 1-10 X X 30-120 3-15 360-480 15-60 360-480

Master Waypoints WanderTime X X 5 1-10 X X 5 1-10 3 15-60 X X 2 1-5 3 2-5 X X 3 2-5

Seek

✓ ✓ X X

✓ ✓ ✓ ✓ ✓ X

Guest Wait Waypoints WanderTime Seek 1-3 X X X 5 1-10 X X X X X X 1-3 X X 30-120 X X 3-15 2 1-5 360-480 3 2-5 15-60 X X X X X

Wait

Staff Waypoints

WanderTime

254

255

Master

Quantity: 5

ENTRANCE

STUDY

MORNING

LIVING

DINING

STAIR

GARDEN

KITCHEN

LUNCH

LIVING

DINING

STAIRG

KITCHEN

ARDEN

LIVING

BATHROOM

DINING

KITCHEN

CHILD

TATAMI

BATH ROOM

EVENING

ADULT

BED ROOM

Guest

BATH ROOM

Quantity: 2

ENTRANCE

ARRIVAL

GARDEN

STUDY

LIVING

STAYING

LIVING

AFTERNOON

LIVING

DINING

17_Koshino House_by Ando

DINING

BATHROOM

BED ROOM

256

257

2 1

5 4

7 16

2 1

5 4

7 16

1 Bathroom B 2 Study 3 Garden A 4 Kitchen 5 Living Room 6 Stair 7 Bathroom A 8 Bedroom Lobby 9 Bedroom A 10 Bedroom B 11 Bedroom C 12 Bedroom D 13 Bedroom E 14 Bedroom F 15 Tatami Room 16 Garden B

17_Koshino House_by Ando

258

259

2 1

5 4

7 16

2 1

5 4

7 16

1 Bathroom B 2 Study 3 Garden A 4 Kitchen 5 Living Room 6 Stair 7 Bathroom A 8 Bedroom Lobby 9 Bedroom A 10 Bedroom B 11 Bedroom C 12 Bedroom D 13 Bedroom E 14 Bedroom F 15 Tatami Room 16 Garden B

17_Koshino House_by Ando

260

261

2 1

5 4

7 16

2 1

5 4

7 16

1 Bathroom B 2 Study 3 Garden A 4 Kitchen 5 Living Room 6 Stair 7 Bathroom A 8 Bedroom Lobby 9 Bedroom A 10 Bedroom B 11 Bedroom C 12 Bedroom D 13 Bedroom E 14 Bedroom F 15 Tatami Room 16 Garden B

17_Koshino House_by Ando

262

263

Room Weights

Room Area & Ratio 17

Living Room Kitchen Study

Original Area Ratio 31.76 16.97 0.23 29.82

Low Resolution Area Ratio 31.76 16.97 0.23 29.82

Mid Resolution Area Ratio 31.76 16.97 0.23 29.82

High Resolution Area Ratio 31.76 16.97 0.25 43.67

Tatami Room Bedroom A Bedroom B Bedroom C Bedroom D Bedroom E Bedroom F Bedroom Lobby

15.40 7.80 7.31 7.31 7.64 7.64 7.64 6.83

0.20

15.40 7.80 7.31 7.31 7.64 7.64 7.64 6.83

0.20

15.40 7.80 7.31 7.31 7.64 7.64 7.64 6.83

0.20

15.40 7.80 7.31 7.51 7.34 7.60 7.63 6.82

0.18

Bathroom AA Bathroom AB Bathroom AC Bathroom B Corridor A Corridor B Corridor C Garden A Garden B Stair

1.65 3.97 8.07 9.90 24.95 10.82 4.63 22.93 85.03 16.18

0.56

1.65 3.97 8.07 9.90 24.95 10.82 4.63 22.93 85.03 16.18

0.56

1.65 3.97 8.07 9.90 24.95 10.82 4.63 22.93 85.03 16.18

0.56

1.65 3.97 8.07 13.21 21.90 10.81 4.28 31.18 85.02 16.17

0.55

Total

334.22

17_Koshino House_by Ando

334.22

356.13

264

265

18_Magney House_by Murcutt Agent Simulation Application Analysis Evaluation

266

Introduction

Photos/Original Plans

Introduction

The Magney House, was completed in 1984, and designed by native Australian architect Glenn Murcutt. The structure can be split into two parts, both along the length and width of the house. Dividing along the length, following the curvilinear spine, the south-facing side consists of the service spaces. From east to west you will find the master bathroom, the main kitchen, a courtyard service counter, the second kitchen, a separate shower, vanity, and toilet, and the laundry room. The north-facing side, from east to west, includes the master bedroom, a living space and dining area, the open courtyard, a secondary living and dining area, two queen bedrooms, and a storage bunk room. 267

18_Magney House_by Murcutt

Agent Simulation

Agent Behaviour Outline There are 4 master agents, of which 2 are children. The master agents undertake daily acitvities. Guests agents, of which there are 2 visit sociallys for events.

18 Seek Patio Living Room Kitchen Dining Master Bedroom Child Bedroom Child Bathroom Master Bathroom Garage Child Living Child Kitchen Child Dining

Wait

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

18_Magney House_by Murcutt

X X X 15-60 360-480 360-480 3-15 3-15 X X X 15-60

Master Waypoints WanderTime 5 1-5 3 15-60 5 1-10 X X 3 2-5 3 2-5 2 1-5 X X 3 1-2 3 15-60 5 1-10 2 5-10

Seek

Wait

✓ ✓ X

✓ X X

✓ ✓ ✓ X X X

X X X 15-60 X X 3-15 3-15 X X X X

Guest Waypoints WanderTime Seek 5 1-5 3 15-60 X X X X X X X X X X X X 3 1-2 X X X X X X

Wait

Staff Waypoints

WanderTime

268

269

Master

Quantity: 4

ENTRANCE

MORNING

ADULT

CHILD

CHILD LIVING

CHILD KITCHEN

EVENING

LUNCH

CHILD

CHILD LIVING

CHILD DINING LIVING

DINING

KITCHEN

GARAGE

CHILD KITCHENC

CHILD DINING LIVING

PATIO

CHILD

CHILD LIVING

CHILD KITCHEN

ADULT

DINING

KITCHEN

GARAGE

PATIO

ADULT

HILD DINING

LIVING

DINING

KITCHEN

GARAGE

PATIO

CHILD

CHILD BEDC

HILD BATH

Guest

ADULT

MASTER BED

MASTER BATH

Quantity: 2

ENTRANCE

ARRIVAL

GARAGE

PATIO

PATIOG

PATIO

LIVING

ARAGE

DINING

CHILD BATH

18_Magney House_by Murcutt

LIVING

MORNING

MASTER BATH

270

271

6 5

4 5

7 9

1 Garage 2 Garage closet 3 Garage wash 4 Children Bedroom B 5 Children Dresser B 6 Children Bedroom A 7 Children Dresser A 8 Children Bathroom B 9 Children Wash 10 Children Bathroom A 11 Children Living Dining 12 Children Kitchen 13 Patio 14 Patio Wash 15 Master Living Dining 16 Master Kitchen

18_Magney House_by Murcutt

17 Master Bedroom 18 Master Dresser 19 Master Bathroom

272

273

6 5

7 9

18_Magney House_by Murcutt

5 2

17 Master Bedroom 18 Master Dresser 19 Master Bathroom

274

275

6 5

7 9

18_Magney House_by Murcutt

5 2

17 Master Bedroom 18 Master Dresser 19 Master Bathroom

276

277

Room Weights

Room Area & Ratio 18

Master Living / Dining Room Child Living / Dining Room Master Kitchen Child Kitchen

Original Area Ratio 27.57 23.35 0.33 6.72 6.36

Low Resolution Area Ratio 29.50 24.90 0.36 3.99 4.67

Mid Resolution Area Ratio 25.95 30.83 0.45 6.12 6.43

High Resolution Area Ratio 18.47 23.32 0.36 5.09 6.33

Master Bedroom Master Dress Rm Master Bathroom Child Bedroom A Child Bedroom B Child Bathroom A Child Bathroom B Child Dress Rm A Child Dress Rm B Children Wash

30.83 2.57 3.44 11.42 11.56 2.34 2.38 0.46 0.46 2.16

0.35

36.63 1.59 3.46 9.77 9.88 1.91 2.22 0.44 0.38 2.14

0.36

17.60 2.26 3.46 6.83 11.55 2.33 2.38 0.33 0.46 1.56

0.31

26.01 2.41 3.44 11.42 11.55 2.33 2.38 1.27 1.27 1.56

0.41

Garage Garage Closet Garage Wash Patio Patio Wash

23.43 3.25 3.13 22.42 6.12

0.30

35.35 2.43 3.60 22.37 5.86

0.27

23.30 3.24 3.13 20.55 3.83

0.22

23.30 3.24 3.12 17.34 1.95

0.21

Total

18_Magney House_by Murcutt

189.97

197.65

168.75

162.46

278

279

19_Paper House_by Ban Agent Simulation Application Analysis Evaluation

19_Paper House_by Ban

280

Introduction

Photos/Original Plans

Introduction Built on the shores of Yamanaka Lake in Yamanashi, the Paper House and its supporting cardboard structure introduced paper architecture as designed by Shigeru Ban. Cheap, light, available in a wide variety of sizes and produced from recycled paper, cardboard had never before been utilized in construction. A 10 square meter plan, it is situated inside a glass skin, forming a long S shape, which at one end extends outside to form a tiny garden and bathroom and then curves back towards the virtually unfurnished interior. 281

19_Paper House_by Ban

Agent Simulation

Agent Behaviour Outline A small residence, consisting of 2 master agents and the occasional guests for social visits. The master agents undertake daily activities related to a resident of the space.

19 Seek Entry Bathinside Bathoutside Living Room Dining Room Kitchen Bedroom Deck

19_Paper House_by Ban

Wait X

✓ ✓ ✓ ✓ ✓ ✓ ✓

X 3-15 3-15 X 15-60 X 360-480 X

Master Waypoints WanderTime X X 2 1-5 2 1-5 3 15-60 2 5-10 5 5-10 3 2-5 5 1-10

Seek

✓ ✓ ✓ ✓ ✓ X X

✓

Guest Wait Waypoints WanderTime Seek 1-3 X X 3-15 2 1-5 3-15 2 1-5 1-3 X X 15-60 2 5-10 X X X X X X X 5 1-10

Wait

Staff Waypoints

WanderTime

282

283

Master

Quantity: 2

ENTRANCE

DECK

MORNING

LIVING

DINING

INSIDE BATHO

AFTERNOON

UTSIDE BATH

LIVING

KITCHEN

DINING

INSIDE BATHO

KITCHEN

DECK

UTSIDE BATH

LIVING

DINING

KITCHEN

Guest

AFTERNOON

EVENING

BED

Quantity: 2

ENTRANCE

ARRIVAL

ENTRANCE

LIVING

DINING

INSIDE BATHO

19_Paper House_by Ban

LIVING

MORNING

DECK

ENTRANCE

UTSIDE BATH

284

285

4 2 3 5 7

1 Deck A 2 Deck B 3 Living Dining Kitchen 4 Enterance 5 Deck C 6 Corridor 7 Bed Corner 8 Outside Bath 9 Inside Bath 10 Deck D

19_Paper House_by Ban

286

287

4 2 3 5 7

1 Deck A 2 Deck B 3 Living Dining Kitchen 4 Enterance 5 Deck C 6 Corridor 7 Bed Corner 8 Outside Bath 9 Inside Bath 10 Deck D

19_Paper House_by Ban

288

289

4 2 3 5 7

1 Deck A 2 Deck B 3 Living Dining Kitchen 4 Enterance 5 Deck C 6 Corridor 7 Bed Corner 8 Outside Bath 9 Inside Bath 10 Deck D

19_Paper House_by Ban

290

291

Room Weights

Room Area & Ratio

Living / Dining / Kitchen Bedroom Corner Inside Bath

Original Area Ratio 97.42 142.99 0.48 9.42

Low Resolution Area Ratio 104.88 140.39 0.48 9.48

Entrance Outside Bath

61.06 2.55

0.12

65.79 2.40

Corridor Deck A Deck B Deck C Deck D

36.26 49.04 28.82 49.74 42.58

0.39

38.20 49.04 28.82 49.74 42.58

Total

519.92

19_Paper House_by Ban

532.43

0.12

Mid Resolution Area Ratio 116.07 115.70

0.53

12.75

0.08

15.18 22.82

0.07

0.38

0.37

42.58

7.85 49.04 28.82 49.74 42.58

459.46

481.11

15.35

21.48 7.88 49.04

0.39

High Resolution Area Ratio 118.56 132.10 0.55 14.38

28.82 49.74

292

293

20_Planar House_by Holl Agent Simulation Application Analysis Evaluation

20_Planar House_by Holl

294

Introduction

Photos/Original Plans

Introduction The home is a series of folds and intersecting planes that allow for simple geometry to become activated within a level of elegant restraint. Originally designed as a residence and private art gallery to showcase important 20th Century contemporary artworks, the home maintains a gallery-like appeal, elevating any lifestyle to a showcase of comfortable living. The home now offers two bedrooms, three baths, an office/studio area, terrazzo concrete floors, Venetian plaster walls, custom cabinetry, a bamboo kitchen, and a superb level of finish throughout. 295

20_Planar House_by Holl

Agent Simulation

Agent Behaviour Outline The 2 master agents undertake day-to-day activities typical of the residence. A staff agent is present, cleaning and serving the master agents. Guests are present occasionally for events.

20 Seek Entry Living Room Kitchen Dining room Gallery Library Courtyard Laundry Bedroom Bathroom Garage Pool Porch Ramp

20_Planar House_by Holl

Wait X

✓ X

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

X X X 15-60 X X X X 360-480 3-15 X X 1-3 X

Master Waypoints WanderTime X X 3 15-60 X X X X 3 1-3 3 15-60 3 5-10 3 1-2 3 2-5 2 1-5 3 1-2 3 5-10 X X

Seek

✓ ✓ X

✓ X

✓ X X X

✓ ✓ ✓ ✓ ✓

Guest Wait Waypoints WanderTime Seek 1-3 X X ✓ 1-3 X X X X X X ✓ 15-60 X X X X X X X X 3 15-60 X X X X X X X X X X X X X 3-15 2 1-5 X X 3 1-2 X X 3 5-10 X 1-3 X X X X ✓

Staff Wait Waypoints WanderTime 1-3 X X X X X X 5 5-10 X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X Cleaning Staff 5 1-3

296

297

Master

Quantity: 2

ENTRANCE MORNING

DINING

LIVING

BATHROOM

KITCHEN

GALLERY

COURTYARD

PORCH

GARAGE

POOL

LIBRARY

RAMP

LUNCH

LAUNDRY

PORCH

DINING

LIVING

RAMP

GARAGE

LAUNDRY

KITCHEN

GALLERY

KITCHEN

EVENING

BATHROOM

COURTYARD

DINING

LYBRARY

POOL

LIBRARY

BEDROOM

LIVING

Staff

BATHROOM

Quantity: 1

ENTRANCE KITCHEN

MORNING

STAFF CLEAN

RAMP

EVENING

KITCHEN

ENTRANCE

Guest

Quantity: 2

ENTRANCE

ARRIVAL

ENTRANCE

GARAGE

DINING

CARPORT

LIVING

BATHROOM

POOL

LIVING

BATHROOM

LEAVING

RAMP

LIBRARY

GARAGE

ENTRANCE

PORCH

RAMP

20_Planar House_by Holl

EVENING

MORNING

LIBRARY

298

299

4 2

14 1

6 15

4 2

11 12

7 14 1

6 15

1 Garage 2 Bedroom 3 Closet 4 Bathroom B 5 Laundry 6 Library 7 Entry 8 Living Room 9 Gallery 10 Kitchen 11 Dining 12 Bathroom A 13 Study 14 Camelback Porch

20_Planar House_by Holl

300

301

4 2

14 1

6 15

4 2

3 5

13 16 14

1 6

1 Garage 2 Bedroom 3 Closet 4 Bathroom B 5 Laundry 6 Library 7 Entry 8 Living Room 9 Gallery 10 Kitchen 11 Dining 12 Bathroom A 13 Study 14 Camelback Porch

20_Planar House_by Holl

302

303

4 2

14 1

6 15

4 2

7 1

16 14 15

1 Garage 2 Bedroom 3 Closet 4 Bathroom B 5 Laundry 6 Library 7 Entry 8 Living Room 9 Gallery 10 Kitchen 11 Dining 12 Bathroom A 13 Study 14 Camelback Porch

20_Planar House_by Holl

304

305

Room Weights

Room Area & Ratio 20

Living Room Dining Study Kitchen Library

Original Area Ratio 51.24 14.67 23.95 0.33 32.91 16.96

Low Resolution Area Ratio 72.48 13.73 30.43 0.37 38.52 16.76

Gallery Bedroom Bathroom AA Bathroom AB Bathroom B Entry A Entry B

26.99 24.34 2.40 7.83 21.53 0.99 9.52

20.61 12.74 2.90 4.81 27.37 0.99 5.43

Closet Lap Pool Pool Court A Pool Court B Laundry Garage Camelback Porch A Camelback Porch B Camelback Porch C Terrace Ramp Outdoor Court A Outdoor Court B Cool Pool

8.38 41.71 4.69 20.40 13.61 39.69 5.85 9.14 25.43 5.29 1.16 15.24 0.78

Total

429.68

20_Planar House_by Holl

0.21

27.44 24.33 1.90

0.16

5.85 10.9 25.46 5.07 0.02 15.11 0.01 461.54

6.68

0.21

21.55 0.99 0.02

1.21 65.71 1.60 3.64 13.78 68.67 0.44

Mid Resolution High Resolution Area Ratio Area Ratio 57.64 51.75 14.30 13.83 0.34 28.86 0.35 27.02 36.96 40.38 16.96 13.60

8.41 15.56 6.28 44.15 13.97 38.66

0.46

4.11

9.14 25.87

0.43

21.82 25.04 1.97 6.97 20.57 0.99 2.50 8.17 72.66 6.55 1.20 13.55 40.00 6.21 9.07 24.87

0.21

7.04 1.17 16.08 0.02

429.68

441.23

5.91 1.17

17.45

0.18

0.46

306

307