Emergence Seminar by Pablo Zamorano

E ME RG E N CE S E MI N AR

D O C U M E N TAT I O N E m e r g e n t Te c h n o l o g i e s & D e s i g n 2 0 1 0

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock P a b l o Za m o r a n o

PROGRAMME: AA EMERGENT TECHNOLOGIES AND DESIGN TERM: 02 STUDENTS NAMES: PIERLUIGI D’ACUNTO NORMAN HACK CAMILA ROCK PABLO ZAMORANO SUBMISSION TITLE:

EMERGENCE SEMINAR - DOCUMENTATION

COURSE TITLE: EMERGENCE SUBMISSION DATE: 21/01/2011 DECLARATION:

We certify that this piece of work is entirely our own and that any quotation or paraphrase from the published or unpublished work of others is duly acknowledged.

SIGNATURE OF STUDENTS:

DATE: 21/01/2011

CONTENTS INTRODUCTION . . . . . . . . . 02 SEQUENCE 01 INTRODUCTION . . . . . . . . 03 POPULATION 1 . . . . . . . . 04 POPULATION 2 . . . . . . . . 06 POPULATION 3 . . . . . . . . 08 POPULATION 4 . . . . . . . . 11 POPULATION 5 . . . . . . . . 15 CONCLUSIONS . . . . . . . . 18 SEQUENCE 02 INTRODUCTION . . . . . . . . 19 POPULATION 6A . . . . . . . . 21 POPULATION 6B . . . . . . . . 24 POPULATION 7 . . . . . . . . 27 POPULATION 8 . . . . . . . . 32 CONCLUSIONS . . . . . . . . 35 SEQUENCE 03 INTRODUCTION . . . . . . . . 36 POPULATION 9 . . . . . . . . 38 POPULATION 10 . . . . . . . . 40 POPULATION 11 . . . . . . . . 43 CONCLUSIONS . . . . . . . . 46 SEQUENCE 04 INTRODUCTION . . . . . . . . 47 POPULATION 12 . . . . . . . . 48 POPULATION 13 . . . . . . . . 50 CONCLUSIONS . . . . . . . . 52

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

INTRODUCTION This paper describes the results of a research project undertaken during the Emergence Seminar of the AA Emergent Technologies and Design Programme (October 2010 to January 2011). Indeed, the goal of this exploration was to understand how evolutionary principles of growth and development could be employed as part of the emergent design processes and in particular for computational evolutionary processes. In fact, the research is based on four main sequences which start from applying standard operations to a simple geometry (primitive) and progressively become more complex in terms growth strategies, as well as techniques and tools applied. In particular, cross-breeding of genomes and creation of hierarchical assemblies were the main strategies used to generate the new populations. Sequence 01 started by choosing a simple geometrical primitive which in this case was the paraboloid. After defining the body plan, a set of basic Rhino operations (Copy, Move, Scale, Mirror and Array Polar) were applied to the primitive in order to create Population 01. Moreover, a Fitness Criteria was defined in order to evaluate the results. In particular, based on the distribution curve of the populations it was possible to define whether a population was fit as a whole or consisted of few fit individuals. Starting from the first population, the other populations were generated based on rule making and growth strategies defined according to the evaluation of the previous populations. In Sequence 02, the individuals created in each generation were analysed looking for an emergent behaviour based on environmental pressure and the growth strategies were modified to improve the overall performance. In addition, mutation techniques such as deletion and duplication were employed in order to achieve variation. Moreover, assemblies and combination of types were created in order to define different levels of hierarchy. As far as Sequence 03 is concerned, a script was developed to automatically generate and evaluate the new populations.

Finally, after modifying the body plan in Sequence 04, a homeobox was introduced in order to control the growing logic and organization of different body parts of the individuals. EVOLUTIONARY COMPUTATION AND EVO-DEVO Evolutionary computation is a research field deriving from the foundings of evolutionary development in biological systems. Generally speaking, evolutionary computation is based on the same biological models on development and evolution that were investigated by scientists such as Darwin (1859) and Bateson (1894) Thomson (1917) and more recently by Gould (1977), Berill and Godwin (1996) and Caroll (2005). Simulation of sexual reproduction, crossover, random allocation of parent genes and mutation applied on the genome are fundamental operations in this processes. Moreover, selection operates on the individuals, by choosing the fittest ones in a specific environmental scenario in which different individuals compete for resources. As a result, just some of them are more likely to survive and propagate their genetic material. As a matter of fact, every living form emerges from two strongly coupled processes operating over maximally differentiated time spans. On the one hand, Embryology describes the growth from an embryo to an adult form; on the other hand, Evolution is related to the process of exchange of genetic information over multiple generations. This study has led to a new field of biological science called Evolutionary Development, (Evo-Devo).

are employed for building different body parts and in modular build animals these switches are used to modify repeated (modular) segments. Moreover, another key concept of Evolutionary Development is the Homeobox: a base-pair sequence of DNA within a group of homeotic genes which encode a protein domain called the homeodomain. Within the homeobox, there are some genes called “activators” - which are in charge of instructing a gene expression at a certain position in the evolving embryo - and some which are the “repressors” - in charge of restricting development of specific parts of the embryo. As a result, the development of different body parts in different animals during evolution is the result of different Hox proteins that are acting on different areas of the whole body plan.

BODY PLAN AND THE HOMEOBOX By definition, the Body plan is a key feature of an organism’s morphology which is a blueprint for the way the body of an organism is laid out. This is one of the most important issues of developmental biology, and explains how radical changes in organisms’ bodies have occurred over geological time. In evolution the specialization of different body parts thus all go back to common ancestral designs. Complexity then builds up over time by a sequence of modifications to existing forms. These can be understood as adaptations and responses to the environmental pressures. Modular switches within the genome

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 started from a paraboloid as the primitive geometry. After defining its body plan, Population 01 of Sequence 01 was created. In particular, each individual was produced by applying to the primitive one of the following standard “Rhino operations”: Move, Copy, Scale 1D, Scale 2D, Rotate, Array Polar and Mirror.

Sequence 01

It is important to mention that the operations and the values which were used to create Population 01 were picked randomly. Moreover, a Fitness Criteria based on the balance of each individual was set in order to analyse the results within every population. The Stability Factor was calculated for each individual using an algorithm which is detailed at the bottom of the current page. GENOME

Body Plan

BP2

BP3

BC BP1

BP4 d

M MOVE (vector(x,y,z)) C COPY (vector(x,y,z), N. of copies) S1 SCALE 1D (copy:T/F, scale axis, scale factor) S2 SCALE 2D (copy:T/F, scale plane, scale factor) R3 ROTATE 3D (copy: T/F, rotation axis, rotation centre point, rotation angle) AP ARRAY POLAR (array plane, rotation centre point, N. of copies, rotation angle) MR MIRROR (copy:T/F, mirror plane, point on mirror plane) [ ] the operation is applied to the last part of the genome only \ separator between different operations TP TIP POINT CM CENTRE OF MASS BC BASE CENTRE BP# BASE POINT The analysis criteria was based on the balance of the object. 1. More unstable 2. More stable In order to achieve a more interesting geometry we decided to start with fitness criteria number 1.

Fitness Criteria

1. More unstable: To achieve a geometry that is on the border of stability. Method: - Get the boundingbox of the individual - Calculate the intersection between the individual and the base of the bounding box - Calculate the convex hull of the intersection points - Calculate centre of mass of the individual (CM) - Project the centre of mass to the ground plane (CM`) - Calculate the distance between CM and CM’ (a) - Kill all the individual whose CM`is outside the convex hull - Calculate the closest point to CM’ on the convex hull (CP) - Calculate the distance between CM’ and CP (b) - Calculate the stability factor a/b - Rank the individuals from bigger to smaller stability factor

CM a CM’

Stability Factor = a b

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Population 01 was created by applying one of the operations mentioned in the previous page to the primitive paraboloid. The same action was repeated 15 times with different operations, therefore, 15 new individuals were created showing variation and differentiation in form between each other.

Sequence 01

In particular, the genome of each individual (based on the list of the operations applied to the primitive) was recorded, following a specific set of rules. This allowed for tracking back the applied operations in a sequential manner.

Population 01

G1-01

S1(F,X,0.75)

G1-09

C((5.0,0,5.0),1)

G1-02

G1-03

S1(F,Y,1.25)

G1-04

S1(F,Z,0.5)

G1-10

C((5.0,5.0,0),1)

S2(F, XY,0.75)

G1-11

S1(F,X,0.75)

G1-05

S2(F, XZ,1.25)

G1-12

S1(F,Y,1.25)\C((0,7.5,0),1)

G1-06

G1-07

C((7.5,0,0),1)

G1-13

S1(F,Z,0.5)\C((0,0,7.5),1)

G1-08

C((0,7.5,0),1)

G1-14

S2(F,XY,0.75)\C((5.0,0,5.0),1)

C((0,0,7.5),1)

G1-15

S2(F,XZ,1.25)\C((5.0,5.0,0),1)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01

Population 01

After generating Population 01, the individuals were ranked according to the fitness criteria, namely the Stability Factor (a/b). In order to analyse this data, a “bell curve” based on the normal distribution of the population was generated. As the graph clearly highlights, the population is roughly following the normal distribution. In particular, it is possible to realise that there are two individuals (G1-09 and G1-14) that could be consider as monsters. In fact, their stability factors are respectively two and four times higher than the values related to the other individuals.

INDIVIDUAL # GENOME G1-01 G1-02 G1-03 G1-04 G1-05 G1-06 G1-07 G1-08 G1-09 G1-10 G1-11 G1-12 G1-13 G1-14 G1-15

1.41 2.84 2.95 2.63 2.84 2.88 2.88 2.89 2.94 2.83 2.83 2.84 6.57 5.31 5.34

b INDIVIDUAL FS = a/b # 4.97 6.21 6.16 4.97 4.98 4.97 4.90 4.99 4.96 3.74 3.74 3.72 4.97 2.45 1.24

G1-030.28 G1-050.45 G1-150.47 G1-130.53 G1-020.56 G1-060.58 G1-070.58 G1-100.58 G1-120.59 G1-010.75 G1-110.75 G1-040.76 G1-081.32 G1-092.16 G1-144.30 0.98 MEAN S.DEVIATION 1.03

S1(F,X,0.75) S1(F,Y,1.25) S1(F,Z,0.5) S2(F, XY,0.75) S2(F, XZ,1.25) C((7.5,0,0),1) C((0,7.5,0),1) C((0,0,7.5),1) C((5.0,0,5.0),1) C((5.0,5.0,0),1) S1(F,X,0.75) S1(F,Y,1.25)\C((0,7.5,0),1) S1(F,Z,0.5)\C((0,0,7.5),1) S2(F,XY,0.75)\C((5.0,0,5.0),1) S2(F,XZ,1.25)\C((5.0,5.0,0),1)

a 1.41 2.84 2.95 2.63 2.84 2.88 2.88 2.89 2.94 2.83 2.83 2.84 6.57 5.31 5.34

b FS = a/b 4.97 6.21 6.16 4.97 4.98 4.97 4.90 4.99 4.96 3.74 3.74 3.72 4.97 2.45 1.24

0.28 0.45 0.47 0.53 0.56 0.58 0.58 0.58 0.59 0.75 0.75 0.76 1.32 2.16 4.30 0.98 1.03

N. DISTRIBUTION 0.31 0.34 0.34 0.35 0.36 0.36 0.36 0.36 0.36 0.38 0.38 0.38 0.37 0.20 0.00

N. DISTRIBUTION 0,45

0,4 0,35 0,3 0,25 0,2 0,15 0,1

0.31 0.34 0.34 0.35 0.36 0.36 0.36 0.36 0.36 0.38 0.38 0.38 0.37 0.20 0.00

0,05 0 0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

After Population 01 was created, the genome of each individual was modified in order to create Population 02. As far as the growth strategy is concerned, according to the fitness criteria of the Stability Factor (ratio between the centre of mass of the individuals and the distance of the projection of it from the border of the footprint), one or two

G2-01

G1-01\MR(T,XY,TP) \M(0,0,-5)

G2-08

G1-08\C(F,Z,1.35)

G2-02

G1-02\S1(F,Z,1.95)

G2-09

G1-09\S1(F,Z,1.15)

G2-03

G2-04

G1-03\AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)

G2-10

G1-10\S1(F,Y,0.31)

Sequence 01

operations were added to each individual in order to create a new population with greater variation. In particular, the main aim of this experiment was to create such a variation within the population in order to achieve a better approximation of the normal distribution.

G1-04\AP(XZ,CM,4,360º)

G2-11

G1-11\C((0,0,3.75),3)

G2-12

Population 02

G2-05

G1-05\S2(F,XY,2)

G1-12\MR(F,XY,TP)\[R3(T,Z,CM,90º)]\ S1(F,Z,0.8)

G2-13

G1-13\C((0,0,5),1)

G2-06

G1-06\MR(T,XZ,CM)

G2-14

G1-14\C((0,0,2),1))

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G2-07

G1-07\C((0,0,7),1)\ [R3(F,Z,CF,90º)]

G2-15

G1-15\R3(F,X,CM,90º)\ AP(XY,CM,3,360º)

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 02

The individuals of Population 02 were ranked according to the Stability Factor (a/b). As the graph clearly highlights, the distribution of Population 02 better approximates the bell curve in comparison to Population 01. This is because specific operations were added to the genomes of each individuals in order to control the overall distribution of the population. As for the standard deviation of Population 02, it is possible to see that the value is lower than the one related to Population 01; this means that generally the Stability Factors of the individuals are close to the mean value. In particular, 9 out of 15 individuals are less than one standard deviation from the mean.

INDIVIDUAL # GENOME G2-01 G2-02 G2-03 G2-04 G2-05 G2-06 G2-07 G2-08 G2-09 G2-10 G2-11 G2-12 G2-13 G2-14 G2-15

1.65 2.84 3.83 5.11 5.53 6.00 6.38 2.90 4.30 6.00 6.42 6.50 8.88 6.12 5.34

S1(F,X,0.75)\MR(T,XY,TP)\M(0,0,-5) S1(F,Y,1.25)\S1(F,Z,1.95) S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2) S2(F, XY,0.75)\AP(XZ,CM,4,360º) S2(F, XZ,1.25)\S2(F,XY,2) C((7.5,0,0),1)\MR(T,XZ,CM) C((0,7.5,0),1)\C((0,0,7),1)\[R3(F,Z,CF,90º)] C((0,0,7.5),1)\C(F,Z,1.35) C((5.0,0,5.0),1)\S1(F,Z,1.15) C((5.0,5.0,0),1)\S1(F,Y,0.31) S1(F,X,0.75)\C((0,0,3.75),3) S1(F,Y,1.25)\C((0,7.5,0),1)\MR(F,XY,TP)\[R3(T,Z,CM,90º)]\S1(F,Z,0.8) S1(F,Z,0.5)\C((0,0,7.5),1)\C((0,0,5),1) S2(F,XY,0.75)\C((5.0,0,5.0),1)\C((0,0,2),1)) S2(F,XZ,1.25)\C((5.0,5.0,0),1)\R3(F,X,CM,90º)\AP(XY,CM,3,360º)

b INDIVIDUAL FS = a/b # 17.49 12.43 6.23 4.98 4.99 4.97 4.90 2.06 2.87 3.74 3.74 3.73 4.97 2.45 2.17

0.09 0.23 0.61 1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49

3 5 15 13 2 6 7 10 12 1 11 4 8 9 14

1.35 MEAN S.DEVIATION 0.69

a 1.65 2.84 3.83 5.11 5.53 6.00 6.38 2.90 4.30 6.00 6.42 6.50 8.88 6.12 5.34

b FS = a/b 17.49 12.43 6.23 4.98 4.99 4.97 4.90 2.06 2.87 3.74 3.74 3.73 4.97 2.45 2.17

0.09 0.23 0.61 1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49 1.35 0.69

N. DISTRIBUTION

N. DISTRIBUTION 0,70

0.11 0.15 0.32 0.51 0.54 0.57 0.58 0.58 0.56 0.54 0.50 0.49 0.47 0.16 0.15

0,60 0,50 0,40 0,30 0,20 0,10 0,00 0,00

0,50

1,00

1,50

2,00

2,50

3,00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01

Population 03 was produced by altering the genome of each individual from Population 02 in order to get a different distribution curve. The values for each operation were also taken randomly.

Population 03

G3-01

G2-01\R3(F,X,CM,90º)\ AP(XY,CM,3,360º)

G3-08

G2-08\C((5,0,0),1)\ S1(F,Z,2)

G3-02

G2-02\R3(F,X,BP2,90º)\ AP(XY,BP3,6,360º)

G3-09

G2-09\ AP(ZX,TP,4,360°)

G3-03

G2-03\S2(F,XZ,0.5)\MR(F,XY,TP)

G3-10

G2-10\R3(T,Y,TP,180°)\ [M(0,0,-5)]

G3-04

G2-04\C((13,0,0),1)\ [R3(T,Z,BC,90°)]\[M(0,0,13)]\ [C(0,-13,0),3))

G3-11

G2-11\AP(ZX,CM,8,360°)\ [R3(T,XY,BC,90°)]

G3-12

G3-05

G3-06

G2-05\S1(F,Z,0.1)

G2-12\S1(F,Z,3)\[MR(T,XY,TP)]\ [S1(F,Z,1/3)]

G3-13

G2-06\ AP(XY,CM,4,360°)\[S2(F,CF,1.5)]

G2-13\C((0,0,10),1)\ [S2(F,XY,2)]

G3-14

G2-14\MR(T,XY,CM)\ R3[(F,Z,TP,75°)]

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G3-07

G2-07\MR(T,XY,CM)

G3-15

G2-15\S2(F,XY,0.4)

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 03

b INDIVIDUAL FS = a/b #

b FS = a/b

N. DISTRIBUTION

N. DISTRIBUTION 2,50E-09

4 5 1 7 15 6 2 13 11 8 12 10 3 14 9

14.30 4.07 -3.51 0.57 12.43 0.05 4.98 5.50 0.91 7.00 5.77 1.21 3.87 2.47 1.54 17.58 7.48 2.35 6.15 2.42 2.54 13.20 4.97 2.64 6.35 2.19 2.90 18.12 4.96 3.64 14.82 3.63 4.08 6.01 1.31 4.58 13.08 1.94 6.69 9.84 0.37 26.53 15.54 1.98E-08 7.83E+08

1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 2.87E-12

1.91E-09 1.91E-09 1.91E-09 2,00E-09 1.91E-09 1.91E-09 1.91E-09 1,50E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 1,00E-09 1.91E-09 1.91E-09 1.91E-09 1.91E-09 5,00E-10 2.87E-12

5.22E+07 MEAN S.DEVIATION 2.02E+08

5.22E+07 2.02E+08

4.30 4.07 -3.51 0.57 12.43 0.05 4.98 5.50 0.91 7.00 5.77 1.21 3.87 2.47 1.54 7.58 7.48 2.35 6.15 2.42 2.54 3.20 4.97 2.64 6.35 2.19 2.90 8.12 4.96 3.64 4.82 3.63 4.08 6.01 1.31 4.58 3.08 1.94 6.69 9.84 0.37 26.53 5.54 1.98E-08 7.83E+08

0,00E+00 0,00E+00

0.61 4.98 1.50 3.08 6.35 6.15 1.02 5.54 7.00 4.30 8.12 7.58 2.46 6.01

b INDIVIDUAL FS = a/b # 0.00 5.50 0.00 1.94 2.19 2.42 0.00 0.00 5.77 4.07 4.96 7.48 0.00 1.31

-3.51 0.05 0.91 1.21 1.54 2.35 2.54 2.64 2.90 3.64 4.08 4.58 6.69 26.53

4 5 1 7 15 6 2 13 11 8 12 10 3 14

4.01 MEAN S.DEVIATION 6.90

a 0.61 4.98 1.50 13.08 6.35 6.15 1.02 15.54 7.00 14.30 18.12 17.58 2.46 6.01

b FS = a/b 0.00 5.50 0.00 1.94 2.19 2.42 0.00 0.00 5.77 4.07 4.96 7.48 0.00 1.31

-3.51 0.05 0.91 1.21 1.54 2.35 2.54 2.64 2.90 3.64 4.08 4.58 6.69 26.53

As can be seen from the first graph, the distribution of Population 03 is totally unbalanced because of the presence of individual G3-09 whose Stability Factor is approximately 1.0E08 times bigger than the values related to the other individuals. As a result, it is possible to see in the first table that the Standard Deviation is much higher than the ones in the other populations. The second graph shows the results of the population without the “monster” (G3-09). In this case, the distribution of the population is closer to the bell curve. However, the range of the distribution is still wide, because of the presence of individual G3-14; in fact, this individual has a Stability Factor which is approximately four times higher than the one related to the closer individual in the ranking.

N. DISTRIBUTION

N. DISTRIBUTION 0,07

0.03 0.05 0.05 0.05 0.05 0.06 0.06 0.06 0.06 0.06 0.06 0.06 0.05 2.81E-04

0.03 0.05 0,06 0.05 0.05 0,050.05 0.06 0.06 0,040.06 0.06 0.06 0,03 0.06 0.06 0,020.05 2.81E-04

2,00E+08

4,00E+08

6,00E+08

8,00E+08

1,00E+09

0,01

4.01 6.90

0,00 -5,00

0,00

5,00

10,00

15,00

20,00

25,00

30,00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 04

Based in our fitness criteria “Factor of Stability” (page 3) we ranked all previous populations and selected the two fittest ones. Population 02 and 03 showed the highest number of fittest individuals or being the most unstables. This was chosen 3to select the most interesting individuals to produce 0.09 population 5 04. 0.23 15 0.61 13 2 6 POP 01 7 10 12 1 11 4 8 14 9

3 5 15 13 2 6 7 10 12 1 11 4 8 9 14

1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49

20.28 1.352

POP 02 0.28 0.45 0.47 0.53 0.56 0.58 0.58 0.58 0.59 0.75 0.75 0.76 1.32 2.16 4.3

3 5 15 13 2 6 7 10 12 1 11 4 8 9 14

3 5 15 13 2 6 7 10 12 1 11 4 8 14 9

RANKING 4 -3.51 5 0.046 1 0.91 7 1.21 15 1.54 6 2.35 2 2.54 130.28 2.640.09 110.45 2.90.23 80.47 3.640.61 120.53 4.081.02 100.56 4.581.11 30.58 6.691.21 0.58 14 26.53 1.3 0.58 9 7830000001.41 0.59 1.5 0.75 783000056 1.6 0.75 1.72 0.7652200003.71.74 1.32 1.79 2.16 2.46 4.3 2.49

14.66

20.28

0.977333333

1.352

3 5 15 13 2 6 7 10 12 1 11 4 8 14 9

4 5 3 5 15 POP 03 1 13 2 6 7 7 10 12 15 1 11 4 8 6 14 9 2 13 11 8 12 10 3 14 9

0.09 0.23 0.61 1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49 20.28 1.352

-3.51 0.046 0.09 0.23 0.61 0.91 1.02 4 1.11 -3.51 5 1.21 0.046 1 1.21 0.91 7 1.3 1.21 15 1.41 1.54 6 1.5 2.35 2 1.54 2.54 13 1.6 2.64 11 2.9 8 3.64 1.72 12 1.74 4.08 10 1.79 4.58 3 2.35 6.69 14 2.46 26.53 9 783000000 2.49 2.54 783000056 2.64 2.9 52200003.7 3.64 4.08 4.58 6.69 26.53 783000000

1 2 3 4 5 6 7 8 4 9 5 10 1 11 7 12 15 13 6 14 2 15 13 11 16 8 17 12 18 10 19 3 20 14 21 9 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

-3.51 0.046 0.09 0.23 0.28 SELECTED POPULATIONS 02-03 0.45 0.47 4 -3.51 4-3.51 -3.51 1 -3.51 0.53 0.046 5 0.046 5 0.046 2 0.046 0.56 3 0.09 3 0.91 0.09 3 0.09 0.58 5 0.23 5 1.21 0.23 4 0.23 0.58 15 0.61 15 1.54 0.61 5 0.28 0.58 1 0.91 1 2.35 0.91 6 0.45 0.59 13 1.02 13 2.54 1.02 7 0.47 0.61 2 1.11 2 2.64 1.11 8 0.53 0.75 6 1.21 6 2.9 1.21 9 0.56 7 1.21 7 3.64 1.21 10 0.58 0.75 7 1.3 7 4.08 1.3 11 0.58 0.76 10 1.41 10 4.58 1.41 12 0.58 0.91 12 1.5 12 6.69 1.5 13 0.59 1.02 15 1.54 1526.531.11 1.54 14 0.61 783000000 1 1.6 1 1.6 15 0.75 1.21 1.21 11 1.72 783000056 11 1.72 16 0.75 1.3 4 1.74 4 1.74 17 0.76 1.32 8 1.79 52200003.7 8 1.79 18 0.91 1.41 6 2.35 6 2.35 19 1.02 1.5 14 2.46 14 2.46 20 1.11 1.54 9 2.49 9 2.49 21 1.21 1.6 2 2.54 2 2.54 22 1.21 1.72 13 2.64 13 2.64 23 1.3 11 2.9 11 2.9 24 1.32 1.74 8 3.64 8 3.64 25 1.41 1.79 12 4.08 12 4.08 26 1.5 2.16 10 4.58 10 4.58 27 1.54 2.35 3 6.69 3 6.69 28 1.6 2.46 14 26.53 14 26.53 29 1.72 2.49 9 783000000 9 2.54 783000000 30 1.74 2.64 31 1.79 2.9 32 2.16 3.64 33 2.35 4.08 34 2.46 4.3 35 2.49 4.58 36 2.54 6.69 37 2.64 26.53 38 2.9 783000000 39 3.64 40 4.08 41 4.3 42 4.58 43 6.69 44 26.53 Emergent Technologies & Design Pierluigi D’Acunto 45 783000000 Norman Hack EMERGENCE SEMINAR Documentation - Jan 2011

Camila Rock Pablo Zamorano

Sequence 01 Population 04

Population 04 was produced by combining the previous populations and selecting the 15 fittest individuals from the two fittest populations (pop02-03).

G4A-01

G4A-02

G4A-08

G4A-09

G2-11

G3-13

G4A-03

G2-04

G3-11

G4A-04

G2-08

G4A-10 G3-08

G4A-05

G3-06

G4A-11 G3-12

G4A-06

G2-14

G4A-12 G3-10

G4A-13 G3-03

G4A-07

G2-09

G4A-14 G3-14

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G3-02

G4A-15 G3-09

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 04

The four fittest individuals from population 04 were selected and recombined selecting the first 50% of the genome from one parent and the last 50% from the other parent to produce two descendants.

G4A-12

C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ R3(T,Y,TP,180°)\ [M(0,0,-5)]

G4A-13

S1(F,Z,0.5)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP, 3,2)\ S2(F,XZ,0.5)\ MR(F,XY,TP)

G4B-01

C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ AP(ZX,TP,4,360°)

G4A-05

S2(F,XY,0.75)\ C((5.0,0,5.0),1)\ C((0,0,2),1))

G4A-15

C((5.0,0,5.0),1)\ S1(F,Z,1.15)\ AP(ZX,TP,4,360°)

G4B-02

S2(F,XZ,0.5)\MR(F,XY,TP) AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\S2(F,XY,0.75)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 04

Population 04 is the result of iterations of the operations selected for sequence 1 applied to the two children produced in the previous experiment.

G4C-01

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°) \C((0.0,3.0,3.0),1)

G4C-08

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ S1(F,Y,3.0)\C(0.0,0.0,12)\ S1(F,Z,1.5)

G4C-02

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\S1(C,Z,0.5)\ [M(0.0,3.0,5.0)]\R3(F,Z,CM,60°)

G4C-09

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\S2(F,XY,0.75)\ S1(F,Z,5)

G4C-10

G4C-03

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\S1(F,Z,3.0)\ R3(T,X,TP,120)\ [M(0.0,-20.0,-15.0)]

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\S2(F,XY,0.75)\ S1(F,Z,12.0)\MR(T,XY,TP)

G4C-11

G4C-04

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°) \C(0.0,0.0,15.0),1)\S1(F,X,0.7)

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\C((15,0,0),1)\ S1(F,X,0.2)

G4C-12

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\ R3(T,Z.BP3,90º)\S1(F,Z,5)

G4C-05

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\MR(T,XY,TP)\ [M(1.5,-0.5,-3.0)]

G4C-13

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\C(0,0,3)

G4C-06

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ R3(T,X,TP,160°)\ [R3(T,Z,CM,180°)]

G4C-14

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\MR(T,XY,BP)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G4C-07

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\S2(F,XY,3)

G4C-15

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\S2(F,XY,0.75)\ S2(F,XY,3)\S1(F,Y,7)

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 04

The individuals of Population 04C were ranked according to the Stability Factor (a/b). As can be seen from the graph, the distribution of Population 04 better approximates the bell curve in comparison to the distribution of Population 03. In fact, even if there is a monster (G4C-03), the standard deviation of Population 04 is 1.0E08 times smaller than the one related to Population 03 and the Stability Factors of the individuals are generally closer to the mean value in comparison to Population 03.

INDIVIDUAL # GENOME G4C-01 G4C-02 G4C-03 G4C-04 G4C-05 G4C-06 G4C-07 G4C-08 G4C-09 G4C-10 G4C-11 G4C-12 G4C-13 G4C-14 G4C-15

4.11 2.57 7.13 8.51 2.60 3.30 3.40 8.66 9.67 1.61 5.52 6.01 0.97 9.77 5.67

C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\C((0.0,3.0,3.0),1) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\S1(C,Z,0.5)\[M(0.0,3.0,5.0)]\R3(F,Z,CM,60°) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\S1(F,Z,3.0)\R3(T,X,TP,120)\[M(0.0,-20.0,-15.0)] C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\C(0.0,0.0,15.0),1)\S1(F,X,0.7) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\MR(T,XY,TP)\[M(1.5,-0.5,-3.0)] C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\R3(T,X,TP,160°)\[R3(T,Z,CM,180°)] C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\S2(F,XY,3) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\S1(F,Y,3.0)\C(0.0,0.0,12)\S1(F,Z,1.5) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\S1(F,Z,5) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\S1(F,Z,12.0)\MR(T,XY,TP) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\R3(T,Z.BP3,90º)\S1(F,Z,5) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C(0,0,3) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\MR(T,XY,BP) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\S2(F,XY,3)\S1(F,Y,7)

b INDIVIDUAL FS = a/b # 10.42 2.85 6.17 5.97 1.78 5.92 5.71 1.98 2.18 4.58 1.97 1.92 5.58 1.94 0.99

0.39 0.92 1.15 1.42 1.46 2.24 2.34 4.37 4.43 4.71 7.87 8.31 9.12 10.16 35.73

14 11 13 7 15 12 9 2 1 8 5 4 10 6 3

6.31 MEAN S.DEVIATION 8.76

a 4.11 2.57 7.13 8.51 2.60 13.30 13.40 8.66 9.67 21.61 15.52 16.01 50.97 19.77 35.67

b FS = a/b 10.42 2.85 6.17 5.97 1.78 5.92 5.71 1.98 2.18 4.58 1.97 1.92 5.58 1.94 0.99

0.39 0.92 1.15 1.42 1.46 2.24 2.34 4.37 4.43 4.71 7.87 8.31 9.12 10.16 35.73 6.31 8.76

N. DISTRIBUTION 3.62E-02 3.77E-02 3.83E-02 3.90E-02 3.91E-02 4.09E-02 4.11E-02 4.44E-02 4.45E-02 4.48E-02 4.48E-02 4.44E-02 4.32E-02 4.13E-02 1.62E-04

N. DISTRIBUTION 0,05

0,05 0,04 0,04 0,03 0,03 0,02 0,02 0,01

3.62E-02 3.77E-02 3.83E-02 3.90E-02 3.91E-02 4.09E-02 4.11E-02 4.44E-02 4.45E-02 4.48E-02 4.48E-02 4.44E-02 4.32E-02 4.13E-02 1.62E-04

0,01 0,00 0,00

5,00

10,00

15,00

20,00

25,00

30,00

35,00

40,00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01

Bases in our fitness criteria “Factor of Stability” (page 3) we selected the four fittest individuals (more stables) from population 04.

G4C-04

C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ AP(ZX,TP,4,360°) \C(0.0,0.0,15.0),1)\ S1(F,X,0.7)

Population 05

G4C-10

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\S2(F,XY,0.75)\ S1(F,Z,12.0)\MR(T,XY,TP)

G4C-06

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ R3(T,X,TP,160°)\ [R3(T,Z,CM,180°)]

G4C-03

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\S1(F,Z,3.0)\ R3(T,X,TP,120)\ [M(0.0,-20.0,-15.0)]

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01

Population 05 is the result of the cross breed of the four individuals selected from population 04.

G5-01

C((5.0,5.0,0),1)\S1(F,Y,0.3)\ AP(ZX,TP,4,360°)\S2(F,XY,0.75)\ S1(F,Z,12.0)\MR(T,XY,TP)

G5-08

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ S2(F,XY,0.75)\S1(F,Z,12.0)\ MR(T,XY,TP)

G5-02

C((5.0,5.0,0),1)\S1(F,Y,0.3)\ AP(ZX,TP,4,360°)\R3(T,X,TP,160°)\ [R3(T,Z,CM,180°)]

G5-09

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ S1(F,Z,3.0)\R3(T,X,TP,120)\ [M(0.0,-20.0,-15.0)]

G5-10

Population 05

G5-03

C((5.0,5.0,0),1)\S1(F,Y,0.3)\ AP(ZX,TP,4,360°)\S1(F,Z,3.0)\ R3(T,X,TP,120°)\[M(0.0,-20.0,-5.0)]

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°) \C(0.0,0.0,15.0),1)\ S1(F,X,0.7)

G5-11

G5-04

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º) \C(0.0,0.0,15.0),1)\S1(F,X,0.7)

C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ S2(F,XY,0.75)\S1(F,Z,12.0)\ MR(T,XY,TP)

G5-12

C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ AP(ZX,TP,4,360°)\ R3(T,X,TP,160°)\ [R3(T,Z,CM,180°)]

G5-05

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ R3(T,X,TP,160°)\ [R3(T,Z,CM,180°)]

G5-13

C(0.0,0.0,15.0),1)\ S1(F,X,0.7)\C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ AP(ZX,TP,4,360°)

G5-06

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S1(F,Z,3.0)\R3(T,X,TP,120)\ [M(0.0,-20.0,-15.0)]

G5-14

S2(F,XY,0.75)\S1(F,Z,12.0)\ MR(T,XY,TP)\C((5.0,5.0,0),1)\ S1(F,Y,0.31)\ AP(ZX,TP,4,360°)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G5-07

C((5.0,5.0,0),1)\S1(F,Y,0.31)\ AP(ZX,TP,4,360°) \C(0.0,0.0,15.0),1)\S1(F,X,0.7)

G5-15

R3(T,X,TP,160°)\ [R3(T,Z,CM,180°)]\ S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Population 05

The individuals of Population 05 were ranked according to the Stability Factor (a/b). As can be seen from the graph, the distribution of Population 05 approximates the normal distribution.

INDIVIDUAL # GENOME G5-01 G5-02 G5-03 G5-04 G5-05 G5-06 G5-07 G5-08 G5-09 G5-10 G5-11 G5-12 G5-13 G5-14 G5-15

ULL ULL ULL ULL 9.11 5.23 1.28 6.01 6.10 6.90 9.06 8.10 4.27 4.28 4.28

C((5.0,5.0,0),1)\S1(F,Y,0.3)\AP(ZX,TP,4,360°)\S2(F,XY,0.75)\S1(F,Z,12.0)\MR(T,XY,TP) C((5.0,5.0,0),1)\S1(F,Y,0.3)\AP(ZX,TP,4,360°)\R3(T,X,TP,160°)\[R3(T,Z,CM,180°)] C((5.0,5.0,0),1)\S1(F,Y,0.3)\AP(ZX,TP,4,360°)\S1(F,Z,3.0)\R3(T,X,TP,120°)\[M(0.0,-20.0,-15.0)] S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\C(0.0,0.0,15.0),1)\S1(F,X,0.7) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\R3(T,X,TP,160°)\[R3(T,Z,CM,180°)] S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S1(F,Z,3.0)\R3(T,X,TP,120)\[M(0.0,-20.0,-15.0)] C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\C(0.0,0.0,15.0),1)\S1(F,X,0.7) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\S2(F,XY,0.75)\S1(F,Z,12.0)\MR(T,XY,TP) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\S1(F,Z,3.0)\R3(T,X,TP,120)\[M(0.0,-20.0,-15.0)] C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\C(0.0,0.0,15.0),1)\S1(F,X,0.7) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)S2(F,XY,0.75)\S1(F,Z,12.0)\MR(T,XY,TP) C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°)\R3(T,X,TP,160°)\[R3(T,Z,CM,180°)] C(0.0,0.0,15.0),1)\S1(F,X,0.7)\C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°) S2(F,XY,0.75)\S1(F,Z,12.0)\MR(T,XY,TP)\C((5.0,5.0,0),1)\S1(F,Y,0.31)\AP(ZX,TP,4,360°) R3(T,X,TP,160°)\[R3(T,Z,CM,180°)]\S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)

b INDIVIDUAL FS = a/b # NULL NULL NULL NULL 11.10 3.29 1.99 1.93 1.05 1.05 0.46 0.29 1.51 1.49 1.49

NULL NULL NULL NULL 0.82 4.56 5.65 8.31 35.1 35.14 41.21 65.13 135.25 136.68 136.68

4 5 13 14 15 6 7 10 9 3 2 12 1 8 11

54.96 MEAN S.DEVIATION 55.64

a NULL NULL NULL NULL 9.11 15.23 11.28 16.01 36.10 36.90 19.06 18.10 204.27 204.28 204.28

b FS = a/b NULL NULL NULL NULL 11.10 3.29 1.99 1.93 1.05 1.05 0.46 0.29 1.51 1.49 1.49

NULL NULL NULL NULL 0.82 4.56 5.65 8.31 35.1 35.14 41.21 65.13 135.25 136.68 136.68 54.96 55.64

N. DISTRIBUTION

NULL NULL NULL NULL 4.47E-03 4.76E-03 4.84E-03 5.05E-03 6.73E-03 6.73E-03 6.95E-03 7.05E-03 2.53E-03 2.44E-03 2.44E-03

NULL NULL 7,00E-03 NULL NULL 6,00E-03 4.47E-03 4.76E-03 5,00E-03 4.84E-03 5.05E-03 6.73E-03 4,00E-03 6.73E-03 6.95E-03 3,00E-03 7.05E-03 2.53E-03 2.44E-03 2,00E-03 2.44E-03

As for the standard deviation of Population 05, the table clearly highlights that the value is much higher than the ones related to the previous populations; this means that overall the Stability Factors of the individuals are not close to the mean value. In particular, only 3 out of 15 individuals are less than one standard deviation from the mean.

8,00E-03

1,00E-03 0,00E+00 0,00

20,00

40,00

60,00

80,00

100,00

120,00

140,00

160,00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 01 Logic diagram

POPULATION 01

POPULATION 02

POPULATION 03

POPULATION 04A

EVALUATION POP. 01,02,03

G1-01

G1-02

G1-03

G2-01

MR \ M

R3 \ AP

POPULATION 04C

4 FITTEST OF POPULATION 4A

POPULATION 05

4 FITTEST OF POPULATION 4C

G3-01

G4A-01

G4C-01

G5-01

G2-02

R3 \ AP

G3-02

G4A-02

S1 \ [M] \ R3

G4C-02

G5-02

AP \ S2

G2-03

S2 \ MR

G3-03

G4A-03

S1 \ R3 \ [M]

G4C-03

G5-03

G1-04

G2-04

C \ [R3] \ [M] \ C

G3-04

G4A-04

C \ S1

G4C-04

1º HALF OF THE GENOME

G5-04

G1-05

G2-05

G3-05

G4A-05

MR \ [M]

G4C-05

G4C-04

G5-05

G1-06

G2-06

AP \ [S2]

G3-06

G4A-06 G4A-12

R3 \ [R3]

G4C-06

G4C-10

G1-07

C \ [R3]

G2-07

G3-07

G4A-07 G4A-13

G4B-01

G4C-07

G4C-06

G1-08

G2-08

C \ S1

G3-08

G4A-08 G4A-05

G4B-02

S1 \ C \ S1

G4C-08

G4C-03

G1-09

G2-09

G3-09

G4A-09 G4A-15

G4C-09

G1-10

G2-10

R3 \ [M]

G3-10

G4A-10

S1 \ MR

G4C-10

2º HALF OF THE GENOME

G1-11

G2-11

AP \ [R3]

G3-11

G4A-11

C \ S1

G4C-11

G4C-04

G5-11

R3 \ S1

G4C-12

G4C-10

G5-12

G5-06 G5-07 G5-08 G5-09 G5-10

G2-12

S1 \ [MR] \ S1

G3-12

G4A-12

G2-13

C \ [S2]

G3-13

G4A-13

G4C-13

G4C-06

G5-13

G1-14

G2-14

MR \ R3

G3-14

G4A-14

G4C-14

G4C-03

G5-14

G1-15

R3 \ AP

G2-15

G4A-15

S2 \ S1

G4C-15

S1 \ C

G1-12

S1 \ C

G1-13

S2 \ C

ASEXUAL REPRODUCTION

CROSS BREEDING STRATEGY

Body Plan

POPULATION 04B

CROSS BREEDING STRATEGY

PRIMITIVE

MR \ [R3] \ S1

ASEXUAL REPRODUCTION

G3-15 ASEXUAL REPRODUCTION

SEXUAL REPRODUCTION

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G5-15 SEXUAL REPRODUCTION

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

For sequence 02 we reworked the genome and body plan to control the grow of the individuals. The mutation strategy were restricted to duplication and deletion only. The breeding strategy was based on the fittests individuals from the population and the envirnonmental pressures were based on a limited ground area (isle) therefore high density was encourage by growing hierarchical assemblies in the vertical plane.

Body Plan

BB6

BB7

TP BB5

BB2 BP2

BB4

BB3

BP3

BC BB1 BP1

BP4 BB0

OPERATIONS: M MOVE C COPY S1 SCALE 1D S2 SCALE 2D R3 ROTATE 3D AP ARRAY POLAR MR MIRROR TP BP BC CM CF

(vector(x,y,z)) (vector(x,y,z), N. of copies) (copy:T/F, scale axis, scale factor) (copy:T/F, scale plane, scale factor) (copy: T/F, rotation axis, rotation centre point, rotation angle) (array plane, rotation centre point, N. of copies, rotation angle) (copy:T/F, mirror plane, point on mirror plane)

TIP POINT BASE POINT BASE CENTRE CENTRE OF MASS CENTRE OF FOOTPRINT

Fitness Criteria BREEDING STRATEGY The breeding strategy was based on the fittest individuals from the previous populations MUTATION STRATEGY The mutation was restricted to two operations: -Duplication -Deletion

ENVIRONMENTAL PRESSURES The envirnoment has a limited amount of ground surface area. Therefore the strategy was to encourage high density by growing hierarchical assemblies in the vertical plane.

Density factor = V AF

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33 55 1515 13 the two All previous generation were ranked 13 and 22 the two less fittest individuals were selected as 66 77 to start sequence 02. 1010 1212 11 1111 44 88 99 1414

0.28 0.45 0.47 0.53 0.56 0.58 0.58 0.58 0.59 0.75 0.75 0.76 1.32 2.16 4.3

33 55 1515 1313 22 66 77 1010 1212 11 1111 44 88 1414 99

0.09 0.09 0.23 0.23 0.61 0.61 1.02 1.02 1.11 1.11 1.21 1.21 1.3 1.3 1.41 1.41 1.5 1.5 1.6 1.6 1.72 1.72 1.74 1.74 1.79 1.79 2.46 2.46 2.49 2.49

3 5 15 13 2 6 7 10 12 1 11 4 8 9 14

Population 03 Population Population 0404

Population 02 3 5 15 13 2 6 7 10 12 1 11 4 8 14 9

Population0303 PopulationPopulation 01

Population Population0202

Population 01 3 5 15 13 2 6 7 10 12 1 11 4 8 9 14

3 5 15 13 2 6 7 10 12 1 11 4 8 14 9

0.28 0.28 0.45 0.45 0.47 0.47 0.53 fittest0.53 and 0.56 0.56 ancestors 0.58 0.58 0.58 0.58 0.58 0.58 0.59 0.59 0.75 0.75 0.75 0.75 0.76 0.76 1.32 1.32 2.16 2.16 4.3 4.3

0.09 0.23 0.61 1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49

Population 04 14 0.39 11 0.92 13 1.15 7 1.42 15 1.46 12 2.24 9 2.34 2 4.37 1 4.43 8 4.71 5 7.87 G3-5 4 8.31 S2(F, XZ,1.25)\ 10 9.12 S2(F,XY,2)\S1(F,Z,0.1) 6 10.16 3 35.73

14144 11115 13131 7 77 15 1515 12126 9 92 2 13 2 11 11 8 88 5 12 5 4 10 4 10103 6 14 6 3 39

44 55 11 77 1515 66 22 1313 1111 88 1212 1010 33 1414 99

-3.51 -3.51 0.28 0.046 0.046 0.45 0.91 0.91 0.47 1.21 1.21 0.53 1.54 1.54 0.56 2.35 2.35 0.58 2.54 2.54 0.58 2.64 2.64 0.58 2.9 2.9 0.59 3.64 3.64 0.75 4.08 4.08 0.75 4.58 4.58 0.76 6.69 6.69 1.32 26.53 26.53 2.16 783000000 783000000 4.3

Population0505 PopulationPopulation 02

-3.51 0.39 0.39 0.046 0.92 0.92 0.91 1.15 1.15 1.21 1.42 1.42 1.54 1.46 1.46 2.35 2.24 2.24 2.54 2.34 2.34 2.64 4.37 4.37 2.9 4.43 4.43 3.64 4.71 4.71 4.08 7.87 7.87 4.58 8.31 8.31 6.69 9.12 9.12 26.53 10.16 10.16 783000000 35.73 35.73

3 5 15 13 2 6 7 10 12 1 11 4 8 14 9

44 55 1313 1414 1515 66 77 1010 99 33 22 1212 11 88 1111

0.09 0.23 0.61 1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49

0.82 0.82 4.56 4.56 5.65 5.65 8.31 8.31 35.1 35.1 35.14 35.14 41.21 41.21 65.13 65.13 135.25 135.25 136.68 136.68 136.68 136.68

4 5 1 7 15 6 2 13 11 8 12 10 3 14 9

Population 05 4 5 13 14 15 6 7 10 9 3 2 G2-3 12 S1(F,Z,0.5)\ 1 AP(XY,BP3,10,360º)\ 8 S2(F,XY,BP3,2) 11

Population 04

0.82 4.56 5.65 8.31 35.1 35.14 41.21 65.13 135.25 136.68 136.68

14 11 13 7 15 12 9 2 1 8 5 4 10 6 3

0.39 4 5 0.92 13 1.15 14 1.42 15 1.46 2.24 6 2.34 7 10 4.37 9 4.43 G5-11 3 4.71 S2(F,XZ,0.5)\MR(F,XY,TP)\ 2 7.87 AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\ 8.31 12 9.12 S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) 1 8 10.16 11 35.73

0.09 0.23 0.61 1.02 1.11 1.21 1.3 1.41 1.5 1.6 1.72 1.74 1.79 2.46 2.49

77 1010 0.046 1212 0.91 1515 1.21 11 1.54 1111 2.35 44 2.54 1515 2.64 11 2.9 1111 4 -3.51 3.64 13 13 5 0.046 4.08 22 3 130.09 13 4.58 5 60.23 6 6.69 3 70.28 7 26.53 14 70.39 7 783000000 5 80.45 8 15 100.47 10 13 70.53 7 Population Population2 04 150.56 15 05 6 120.58 12 7 150.58 15 14 0.39 4 10 10.58 1 5 11 0.92 12 110.59 11 13 13 1.15 15 40.61 4 14 7 1.42 1 80.75 8 15 0.82 15 1.46 11 90.75 9 12 2.24 6 4.56 4 120.76 12 9 2.34 7 5.65 15 90.82 9 10 8.31 2 4.37 1 60.91 6 9 35.1 1 4.43 11 140.92 14 13 91.02 9 3 35.14 8 4.71 2 21.11 2 2 41.21 5 7.87 13 131.15 13 4 8.31 12 65.13 6 111.21 11 10 9.12 1 135.25 7 81.21 8 8 136.68 6 10.16 7 1.3 1212 11 136.68 3 35.73 8 141.32 14 10 21.41 2 7 11.42 1 15 61.46 6 Population 03 12 1.5 1010 15 81.54 8 1 -3.51 7 1.6 7 11 0.046 31.72 3 4 0.91 51.74 5 8 1.21 41.79 4 9 1.54 102.16 10 12 102.24 10 2.35 9 62.34 6 2.54 6 142.35 14 14 2.64 92.46 9 2.9 9 32.49 3 2 3.64 32.54 3 13 4.08 22.64 2 11 4.58 2.9 1212 8 13.64 1 6.69 12 84.08 8 26.53 14 4.3 1111 783000000 2 94.37 9 1 4.43 6 4.56 4.58 Population 05 10 8 4.71 7 5.65 3 6.69 5 7.87 4 8.31 10 8.31 10 0.82 9.12 6 4.56 10.16 14 5.65 26.53 9 8.31 35.1 3 35.14 35.1 3 35.73 2 35.14 41.21 41.21 12 S2(F,XZ,0.5)\MR(F,XY,TP)\ 65.13 65.13 1 AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\ 135.25 8135.25 S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2)136.68 11136.68 136.68 9136.68 783000000

G3-9

5 1 7 15 6 2 13 11 8 12 10 3 14 9

0.58 0.58 0.58 0.58 0.59 0.59 0.61 0.61 0.75 0.75 0.75 0.75 0.76 0.76 0.82 0.82 0.91 0.91 0.92 0.92 4 1.02 1.02 5 1.11 1.11 3 1.15 1.15 5 1.21 1.21 3 1.21 1.21 14 1.3 1.3 5 1.32 1.32 15 1.41 1.41 13 1.42 1.42 2 1.46 1.46 6 1.5 1.5 1.54 7 1.54 1.6 1.6 10 1.72 12 1.72 1.74 15 1.74 1.79 1 1.79 2.16 11 2.16 2.24 4 2.24 2.34 15 2.34 2.35 1 2.35 2.46 11 2.46 2.49 13 2.49 2.54 2 2.54 2.64 13 2.64 2.9 2.9 6 3.64 7 3.64 4.08 7 4.08 4.3 4.3 8 4.37 10 4.37 4.43 7 4.43 4.56 15 4.56 4.58 12 4.58 4.71 4.71 15 5.65 5.65 1 6.69 6.69 11 7.87 7.87 4 8.31 8.31 8 8.31 8.31 9 9.12 9.12 12 10.16 10.16 9 26.53 26.53 6 35.1 35.1 14 35.14 35.14 9 35.73 35.73 2 41.21 41.21 13 65.13 65.13 11 135.25 135.25 8 136.68 136.68 12 136.68 136.68 14 783000000 783000000 2 1 6 10 8 7 3 5 4 10 10 6 14 9 3 3 2 12 1 8 11 9

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11 11 11 44 88 99 12 12 99 66 14 14 -3.51 99 0.046 22 0.0913 13 0.23 11 11 0.28 88 0.3912 12 0.4514 14 0.47 22 0.53 11 0.56 66 0.5810 10 0.58 88 0.58 77 0.59 33 0.61 55 0.75 44 10 0.7510 10 0.7610 0.82 66 14 0.9114 0.92 99 1.02 33 1.11 33 1.15 22 12 1.2112 1.21 11 1.3 88 11 1.32 11 1.41 99

Sequence 02 Population 06

1.42 1.46 1.5 1.54 1.6 1.72 1.74 1.79 2.16 2.24 2.34 2.35 2.46 2.49 2.54 2.64 2.9 3.64 4.08 4.3 4.37 4.43 4.56 4.58 4.71 5.65 6.69 7.87 8.31 8.31 9.12 10.16 26.53 35.1 35.14 35.73 41.21 65.13 135.25 136.68 136.68 783000000

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

Population 06A Population 06A was generated from the cross breed of the four selected ancestors using the first 50% of the genome from one parent and the last 50% from the other parent to produce twenty descendants.

G6A-01

S2(F, XZ,1.25)\S2(F,XY,2)\ S2(F,XY,BP3,2)

G6A-11

S2(F,XZ,0.5)\ MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S1(F,Z,0.1)

G6A-02

S2(F, XZ,1.25)\ S2(F,XY,2)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\ C((15,0,0),1)\ S1(F,X,0.2)

G6A-12

S2(F,XZ,0.5)\ MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)

G6A-03

S2(F, XZ,1.25)\ S2(F,XY,2)\ AP(ZX,TP,4,360°)

G6A-13

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ AP(ZX,TP,4,360°)

G6A-04

S2(F,XY,BP3,2)\ S2(F, XZ,1.25)\ S2(F,XY,2)

G6A-14

S1(F,Z,0.1)\S2(F,XZ,0.5)\ MR(F,XY,TP)\ AP(XY,BP3,10,360º)

G6A-05

AP(ZX,TP,4,360°)\ S2(F, XZ,1.25)\ S2(F,XY,2)

G6A-15

AP(ZX,TP,4,360°)\ S2(F,XZ,0.5)\ MR(F,XY,TP)\ AP(XY,BP3,10,360º)

G6A-06

S1(F,Z,0.5)\ AP(XY,BP3,10,360º)\ S1(F,Z,0.1)

G6A-16

C((5.0,0,5.0),1)\ S1(F,Z,1.15)\ S1(F,Z,0.1)

G6A-07

S1(F,Z,0.5)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\ C((15,0,0),1)\ S1(F,X,0.2)

G6A-17

C((5.0,0,5.0),1)\ S1(F,Z,1.15)\ S2(F,XY,BP3,2)

G6A-08

S1(F,Z,0.5)\ AP(XY,BP3,10,360º)\ AP(ZX,TP,4,360°)

G6A-18

C((5.0,0,5.0),1)\ S1(F,Z,1.15)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\C((15,0,0),1)\ S1(F,X,0.2)

G6A-09

S1(F,Z,0.1)\S1(F,Z,0.5)\ AP(XY,BP3,10,360º)

G6A-19

S1(F,Z,0.1)\C((5.0,0,5.0),1)\ S1(F,Z,1.15)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G6A-10

AP(ZX,TP,4,360°)\ S1(F,Z,0.5)\ AP(XY,BP3,10,360º)

G6A-20

S2(F,XY,BP3,2)\ C((5.0,0,5.0),1)\ S1(F,Z,1.15)

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02 Population 06

The individuals of Population 06A were ranked according to the Stability Factor (a/b). By this time, some of the individuals -8 from 20- are NULL since they could not be evaluated -either their parts were separated between each other, or they were unbalanced-, in consequence those individuals would be killed. As far as the distribution of the curve concerns, despite it is better approximates the bell curve in comparison to the previous populations, there is still a “monster” which is unbalancing the overall distribution of the population, with a Factor of Stability approximately 2 times bigger than the closer individual in the table. On the other hand, the standard deviation of Population 06A, is much smaller than the ones on the previous populations, this means that the values are closer to the mean value.

INDIVIDUAL # GENOME G6A-01 G6A-02 G6A-03 G6A-04 G6A-05 G6A-06 G6A-07 G6A-08 G6A-09 G6A-10 G6A-11 G6A-12 G6A-13 G6A-14 G6A-15 G6A-16 G6A-17 G6A-18 G6A-19 G6A-20 a

0.06 0.06 0.17 2.73 3.45 0.61 2.60 1.59 6.05 5.50 6.11 6.10 ULL ULL ULL ULL ULL ULL ULL ULL

S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2) S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) S2(F, XZ,1.25)\S2(F,XY,2)\AP(ZX,TP,4,360°) S2(F,XY,BP3,2)\S2(F, XZ,1.25)\S2(F,XY,2) AP(ZX,TP,4,360°)\S2(F, XZ,1.25)\S2(F,XY,2) S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S1(F,Z,0.1) S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) S1(F,Z,0.5)\AP(XY,BP3,10,360º)\AP(ZX,TP,4,360°) S1(F,Z,0.1)\S1(F,Z,0.5)\AP(XY,BP3,10,360º) AP(ZX,TP,4,360°)\S1(F,Z,0.5)\AP(XY,BP3,10,360º) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S1(F,Z,0.1) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\AP(ZX,TP,4,360°) S1(F,Z,0.1)\S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º) AP(ZX,TP,4,360°)\S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º) C((5.0,0,5.0),1)\S1(F,Z,1.15)\S1(F,Z,0.1) C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2) C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) S1(F,Z,0.1)\C((5.0,0,5.0),1)\S1(F,Z,1.15) S2(F,XY,BP3,2)\C((5.0,0,5.0),1)\S1(F,Z,1.15)

b INDIVIDUAL FS = a/b # 9.91 9.11 7.10 24.71 19.81 2.45 10.10 4.40 7.27 5.22 4.90 2.44 NULL NULL NULL NULL NULL NULL NULL NULL

0.01 0.01 0.02 0.11 0.17 0.25 0.26 0.36 0.83 1.05 1.25 2.50 NULL NULL NULL NULL NULL NULL NULL NULL

6 9 11 4 1 16 12 7 20 2 17 18 3 5 8 10 13 14 15 19

0.57 MEAN S.DEVIATION 0.74

a 0.06 0.06 0.17 2.73 3.45 0.61 2.60 1.59 6.05 5.50 6.11 6.10 NULL NULL NULL NULL NULL NULL NULL NULL

b FS = a/b 9.91 9.11 7.10 24.71 19.81 2.45 10.10 4.40 7.27 5.22 4.90 2.44 NULL NULL NULL NULL NULL NULL NULL NULL

0.01 0.01 0.02 0.11 0.17 0.25 0.26 0.36 0.83 1.05 1.25 2.50 NULL NULL NULL NULL NULL NULL NULL NULL

N. DISTRIBUTION 0.41 0.41 0.41 0.44 0.47 0.49 0.49 0.52 0.51 0.44 0.35 0.02 NULL NULL NULL NULL NULL NULL NULL NULL

N. DISTRIBUTION 0,60

0,50

0,40

0,30

0,20

0,10

0,00 0,00

0.41 0.41 0.41 0.44 0.47 0.49 0.49 0.52 0.51 0.44 0.35 0.02 NULL NULL NULL NULL NULL NULL NULL 0,50 NULL

1,00

1,50

2,00

2,50

3,00

0.57 0.74

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

Population 06

DUPLICATION

DELETION

1 S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2)

2 S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2)

2 S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2)\C((15,0,0),1)\S1(F,X,0.2)

3 S2(F, XZ,1.25)\S2(F,XY,2)\AP(ZX,TP,4,360°)

kill

4 S2(F,XY,BP3,2)\S2(F, XZ,1.25)\S2(F,XY,2)

4 S2(F, XZ,1.25)\S2(F,XY,2)

5 AP(ZX,TP,4,360°)\S2(F, XZ,1.25)\S2(F,XY,2)

kill

6 S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S1(F,Z,0.1)

7 S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2)

8 S1(F,Z,0.5)\AP(XY,BP3,10,360º)\AP(ZX,TP,4,360°)

kill

9 S1(F,Z,0.1)\S1(F,Z,0.5)\AP(XY,BP3,10,360º)

10 AP(ZX,TP,4,360°)\S1(F,Z,0.5)\AP(XY,BP3,10,360º)

kill

11 S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S1(F,Z,0.1)

kill

12 S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)

13 S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\AP(ZX,TP,4,360°)

kill

14 S1(F,Z,0.1)\S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)

kill

15 AP(ZX,TP,4,360°)\S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)

kill

16 C((5.0,0,5.0),1)\S1(F,Z,1.15)\S1(F,Z,0.1)

17 C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2)

17 C((5.0,0,5.0),1)\C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2)

18 C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2)

19 S1(F,Z,0.1)\C((5.0,0,5.0),1)\S1(F,Z,1.15)

kill

20 S2(F,XY,BP3,2)\C((5.0,0,5.0),1)\S1(F,Z,1.15)

20 S2(F,XY,BP3,2)\S2(F,XY,BP3,2)\C((5.0,0,5.0),1)\S1(F,Z,1.15)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

In order to control the distribution of variations according to our chosen strategy we mutated population 06A, evaluated it and generated population 06B.

G6B-01

S2(F, XZ,1.25)\S2(F,XY,2)\ S2(F,XY,BP3,2)

G6B-07

S2(F,XZ,0.5)\MR(F,XY,TP)\ AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)

G6B-02

S2(F, XZ,1.25)\S2(F,XY,2)\ S2(F,XY,BP3,2)\C((15,0,0),1)\ S1(F,X,0.2)

G6B-08

C((5.0,0,5.0),1)\S1(F,Z,1.15)\S1(F,Z,0.1)

Population 06B

G6B-03

S2(F, XZ,1.25)\S2(F,XY,2)

G6B-09

C((5.0,0,5.0),1)\C((5.0,0,5.0),1)\ S1(F,Z,1.15)\S2(F,XY,BP3,2)

G6B-04

G6B-05

S1(F,Z,0.5)\ AP(XY,BP3,10,360º)\ S1(F,Z,0.1)

G6B-06

S1(F,Z,0.5)\AP(XY,BP3,10,360º)\ S2(F,XY,BP3,2)\ S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2)

G6B-10

C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2)\ S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2)

S1(F,Z,0.1)\S1(F,Z,0.5)\ AP(XY,BP3,10,360º)

G6B-11

S2(F,XY,BP3,2)\ S2(F,XY,BP3,2)\C((5.0,0,5.0),1)\ S1(F,Z,1.15)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

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Sequence 02

Population 06

After the mutation strategy applied to Population 6A, the resulting Population 06B was ranked according to the same fitness criteria, Stability Factor (a/b).

INDIVIDUAL # GENOME G6B-01 G6B-02 G6B-03 G6B-04 G6B-05 G6B-06 G6B-07 G6B-08 G6B-09 G6B-10 G6B-11

0.06 0.06 3.45 0.61 2.60 6.04 3.54 1.59 3.74 6.10 8.90

b INDIVIDUAL FS = a/b # 9.91 9.11 19.81 2.45 10.10 17.17 9.95 4.40 6.46 2.44 0.09

0.01 4 0.01 6 0.17 1 0.25 8 0.26 7 0.35 11 0.36 3 0.36 5 0.58 2 2.50 10 98.89 9 9.43 MEAN S.DEVIATION 29.68

S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2) S2(F, XZ,1.25)\S2(F,XY,2)\S2(F,XY,BP3,2)\C((15,0,0),1)\S1(F,X,0.2) S2(F, XZ,1.25)\S2(F,XY,2) S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S1(F,Z,0.1) S1(F,Z,0.5)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) S1(F,Z,0.1)\S1(F,Z,0.5)\AP(XY,BP3,10,360º) S2(F,XZ,0.5)\MR(F,XY,TP)\AP(XY,BP3,10,360º)\S2(F,XY,BP3,2) C((5.0,0,5.0),1)\S1(F,Z,1.15)\S1(F,Z,0.1) C((5.0,0,5.0),1)\C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2) C((5.0,0,5.0),1)\S1(F,Z,1.15)\S2(F,XY,BP3,2)\S2(F,XY,0.75)\C((15,0,0),1)\S1(F,X,0.2) S2(F,XY,BP3,2)\S2(F,XY,BP3,2)\C((5.0,0,5.0),1)\S1(F,Z,1.15)

a 0.06 0.06 3.45 0.61 2.60 6.04 3.54 1.59 3.74 6.10 8.90

b FS = a/b 9.91 9.11 19.81 2.45 10.10 17.17 9.95 4.40 6.46 2.44 0.09

0.01 0.01 0.17 0.25 0.26 0.35 0.36 0.36 0.58 2.50 98.89 9.43 29.68

N. DISTRIBUTION

N. DISTRIBUTION 1,60E-02

1.28E-02 1.28E-02 1.28E-02 1.28E-02 1.28E-02 1.28E-02 1.28E-02 1.28E-02 1.29E-02 1.31E-02 1.43E-04

1,40E-02 1,20E-02 1,00E-02 8,00E-03 6,00E-03

As can be seen from the graph, the distribution of the curve is even more unbalanced than Population 6A, that is because some parts of the genome that were manipulated in the mutation strategy did not respond to the fitness criteria, even the presence of a “monster” increased considerably the standard deviation and as a consequence of that the values are farther to the mean.

4,00E-03 2,00E-03 0,00E+00 0,00

20,00

40,00

60,00

80,00

100,00

120,00

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Sequence 02

The 6 lowest level individuals were selected to start the next population. We defined the lower levels as the individuals with the least amount of components on it.

G6B-01

S2(F, XZ,1.25)\S2(F,XY,2)\ S2(F,XY,BP3,2)

G6B-03

S2(F, XZ,1.25)\S2(F,XY,2)

Population 07

G6B-11

S2(F,XY,BP3,2)\ S2(F,XY,BP3,2)\C((5.0,0,5.0),1)\ S1(F,Z,1.15)

G6B-02

S2(F, XZ,1.25)\S2(F,XY,2)\ S2(F,XY,BP3,2)\C((15,0,0),1)\ S1(F,X,0.2)

G6B-08

C((5.0,0,5.0),1)\S1(F,Z,1.15)\ S1(F,Z,0.1)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G6B-09

C((5.0,0,5.0),1)\C((5.0,0,5.0),1)\ S1(F,Z,1.15)\S2(F,XY,BP3,2)

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

Population 07 was created from the hierarchical assemblies of the 6 lowest level individuals from population 06. The assemblies respond to our selected environmental pressure growing always in the vertical plane. Selecting the individuas with the least amount of components on them we were ables to get a more controlled grow.

G7-01

G6B-11\M(20,20,15)\\G6B-09\ [AP(XY,BP3,4,360)]

G7-08

G6B-03\R3(F,Y,BB1,90)\ AP(XY,BB2,6,360)\\ G6B-01\M(0,0,10)

G7-02

G7-03

G6B-03\M(12,12,8)\\G6B-01\ MR(T,XY,TP)

G7-09

G6B-09\AP(ZY,BB7,6,160)

Population 07

G6B-02\\G6B-08\M(0,12,8)\ [S1(F,Z,10)\R3(T,Y,BB7,60)]

G7-10

G6B-02\C(30,0,0)\\ G6B-11\M(0,0,10)

G7-11

G7-04

G6B-03\MR(T,XY,BB6)\\ G6B-01\M(-12,-12-20)

G6B-09\MR(T,ZX,TP)\\ G6B-02\S1(F,Z,4)

G7-12

G7-05

G6B-08\S1(F,Z,15)\ AP(XY,BBC,3,360°)\MR(T,XY,BB4)\\ G6B-09\MR(T,XY,BB4)

G6B-08\S1(F,Z,8)\ C(0,0,5)\C(0,5,0)\\G6B-03\ R3(F,XZ,BB4,90)

G7-13

G7-06

G6B-09\MR(F,XY,BB5)\ AP(XY,BB5,5,360°)\M(0,0,-18)\\ G6B-08\M(-25,0,24)

G6B-01\ R3(F,Y,BB4,90)\M(0,0,-10)\ S1(X,BB0,0.5)\\G6B-02\ S1(X,BB0,0.5)\AP(XY,CM,8,200º)

G7-14

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\\ G6B-11\AP(XZ,BB4,4,100º)

G7-07

G6B-02\C((0,0,8),1)\[R3(F,Z,TP,20)]\ [C((0,0,8),1)]\[R3(F,Z,TP,20)]\ [C((0,0,8),1)]\[R3(F,Z,TP,20)]\ [C((0,0,8),1)]\[R3(F,Z,TP,20)]\ [C((0,0,8),1)]\[R3(F,Z,TP,20)]

G7-15

G6B-09\S1(F,Z,8)\ C(0,0,5)\C(0,5,0)]\\ G6B-08\R(F,Y,BB4,90)\M(0,0,-22)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

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Sequence 02

Population 07

Population 07, is a result of the the 6 lowest level individuals of Population 06B. The evaluation and ranking of this population was according to the Environmental Pressure explained in the first part of the current sequence. After applying the Assembly Strategy between the selected individuals of Population 06B, it is possible to see that the curve is better approximates, although there is one “monster” which is increasing considerably the Standard deviation and as a result the values are farther from the mean.

INDIVIDUAL # GENOME G7-01 G7-02 G7-03 G7-04 G7-05 G7-06 G7-07 G7-08 G7-09 G7-10 G7-11 G7-12 G7-13 G7-14 G7-15

E+07 E+06 E+07 E+07 E+07 E+07 E+07 E+07 E+06 E+07 E+07 E+07 E+07 E+07 E+08

G6B-20\M(20,20,15)\\G6B-17\[AP(XY,BP3,4,360)] G6B-04\M(12,12,8)\\G6B-01\MR(T,XY,TP) G6B-02\\G6B-16\M(0,12,8)\[S1(F,Z,10)\R3(T,Y,BB7,60)] G6B-04\MR(T,XY,BB6)\\G6B-01\M(-12,-12-20) G6B-16\S1(F,Z,15)\AP(XY,BBC,3,360°)\MR(T,XY,BB4)\\G6B-17\MR(T,XY,BB4) G6B-17\MR(F,XY,BB5)\AP(XY,BB5,5,360°)\M(0,0,-18)\\G6B-16\M(-25,0,24) G6B-02\C((0,0,8),1)\[R3(F,Z,TP,20)]\[C((0,0,8),1)]\[R3(F,Z,TP,20)]\[C((0,0,8),1)]\[R3(F,Z,TP,20)]\[C((0,0,8),1)]\[R3(F,Z,TP,20)]\[C((0,0,8),1)]\[R3(F,Z,TP,20)] G6B-04\R3(F,Y,BB1,90)\AP(XY,BB2,6,360)\\G6B-01\M(0,0,10) G6B-17\AP(ZY,BB7,6,160) G6B-02\C(30,0,0)\\G6B-20\M(0,0,10) G6B-17\MR(T,ZX,TP)\\G6B-02\S1(F,Z,4) G6B-16\S1(F,Z,8)\C(0,0,5)\C(0,5,0)\\G6B-04\R3(F,XZ,BB4,90) G6B-01\R3(F,Y,BB4,90)\M(0,0,-10)\S1(X,BB0,0.5)\\G6B-02\S1(X,BB0,0.5)\AP(XY,CM,8,200º) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\\G6B-20\AP(XZ,BB4,4,100º) G6B-17\S1(F,Z,8)\C(0,0,5)\C(0,5,0)]\\G6B-6\R3(F,Y,BB4,90)\M(0,0,-22)

AF INDIVIDUAL V/AF# 2.00E+05 5.41E+04 2.00E+05 2.00E+05 1.80E+05 1.04E+05 3.77E+05 3.30E+05 2.78E+04 1.06E+05 8.29E+04 4.76E+04 2.25E+04 8.00E+04 1.80E+05

1564 1703 1848 2122 213 10 2267 2416 2621 279 12 425 11 4265 506 13 756 15 8249 1221 14

MEAN 407 S.DEVIATION 306

V/AF

N. DISTRIBUTION

3.13E+07 9.23E+06 3.68E+07 4.26E+07 3.84E+07 2.36E+07 9.12E+07 8.67E+07 7.78E+06 4.51E+07 3.54E+07 2.41E+07 1.70E+07 6.59E+07 2.20E+08

2.00E+05 5.41E+04 2.00E+05 2.00E+05 1.80E+05 1.04E+05 3.77E+05 3.30E+05 2.78E+04 1.06E+05 8.29E+04 4.76E+04 2.25E+04 8.00E+04 1.80E+05

156 170 184 212 213 226 241 262 279 425 426 506 756 824 1221

9.32E-04 9.67E-04 1.00E-03 1.06E-03 1.07E-03 1.10E-03 1.13E-03 1.17E-03 1.19E-03 1.30E-03 1.30E-03 1.24E-03 6.80E-04 5.15E-04 3.78E-05

407 306

N. DISTRIBUTION

1,40E-03 1,20E-03 1,00E-03 8,00E-04 6,00E-04 4,00E-04

9.32E-04 9.67E-04 1.00E-03 1.06E-03 1.07E-03 1.10E-03 1.13E-03 1.17E-03 1.19E-03 1.30E-03 1.30E-03 1.24E-03 6.80E-04 5.15E-04 3.78E-05

2,00E-04 0,00E+00 0,00E+00 2,00E+02 4,00E+02 6,00E+02 8,00E+02 1,00E+03 1,20E+03 1,40E+03

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

After applying our kill strategy (individuals with a ratio below the mean value) we selected the survivors (individuals with a ratio above the mean value)

G7-11

G6B-09\MR(T,ZX,TP)\\ G6B-02\S1(F,Z,4)

G7-05

G6B-08\S1(F,Z,15)\ AP(XY,BBC,3,360°)\MR(T,XY,BB4)\\ G6B-09\MR(T,XY,BB4)

Population 08

G7-13

G6B-01\ R3(F,Y,BB4,90)\M(0,0,-10)\ S1(X,BB0,0.5)\\G6B-02\ S1(X,BB0,0.5)\AP(XY,CM,8,200º)

G7-15

G6B-09\S1(F,Z,8)\ C(0,0,5)\C(0,5,0)]\\ G6B-08\R(F,Y,BB4,90)\M(0,0,-22)

G7-09

G6B-09\AP(ZY,BB7,6,160)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

G7-14

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\\ G6B-11\AP(XZ,BB4,4,100º)

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

Population 08

In order to decrease the Standard Deviation to obtain a fittest population a killing strategy was applied to individuals of Population 07. After killing the individuals with the ratio below the mean value, it is possible to see that the Standard deviation decreases considerable, therefore, the values are now closer to the mean value which means that the evaluation of these individuals approximates better the Normal Distribution.

INDIVIDUAL # GENOME G7-05 G7-09 G7-11 G7-13 G7-14 G7-15

a +07 +07 +07 +07 +08 +07

G6B-16\S1(F,Z,15)\AP(XY,BBC,3,360°)\MR(T,XY,BB4)\\G6B-17\MR(T,XY,BB4) G6B-17\AP(ZY,BB7,6,160) G6B-17\MR(T,ZX,TP)\\G6B-02\S1(F,Z,4) G6B-01\R3(F,Y,BB4,90)\M(0,0,-10)\S1(X,BB0,0.5)\\G6B-02\S1(X,BB0,0.5)\AP(XY,CM,8,200º) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\\G6B-20\AP(XZ,BB4,4,100º) G6B-17\S1(F,Z,8)\C(0,0,5)\C(0,5,0)]\\G6B-6\R3(F,Y,BB4,90)\M(0,0,-22)

bINDIVIDUAL FS = a/b # 1.06E+05 4.76E+04 8.29E+04 8.00E+04 1.80E+05 2.25E+04

FS = a/b

N. DISTRIBUTION

11 3.974.51E+07 13 4.152.41E+07 4.63 5 3.54E+07 7.17 9 6.59E+07 14 8.752.20E+08 15 9.361.70E+07

1.06E+05 4.76E+04 8.29E+04 8.00E+04 1.80E+05 2.25E+04

3.97 4.15 4.63 7.17 8.75 9.36

1.02E-01 1.10E-01 1.29E-01 1.56E-01 1.00E-01 7.54E-02

MEAN 6.34 S.DEVIATION 2.41

6.34 2.41

N. DISTRIBUTION

0.18

1.02E-01

0.16 1.10E-01 1.29E-01 1.56E-01 0.14 1.00E-01 7.54E-02

0.12 0.10 0.08 0.06 0.04 0.02 0.00

0.00

2.00

4.00

6.00

8.00

10.00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

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Sequence 02

The two fittest individuals from the previous survivors were selected based on the stability factor. The two individuals represent the more stable individuals from the previous population.

G7-15

G6B-09\S1(F,Z,8)\ C(0,0,5)\C(0,5,0)]\\ G6B-08\R(F,Y,BB4,90)\M(0,0,-22)

Population 08

G7-14

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\\ G6B-11\AP(XZ,BB4,4,100º)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 02

Population 08 sexually produced by taking one part of the assembly from the first parent and applying operations to it and then assembled with one part of the assembly from the second parent plus random operations.

G8-01

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\ [AP(XY,BB0,6,360º)\\G6B-09\ S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\ [S2(F,XZ,BB0,5)]\M(-20,0,-20)

G8-08

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)] \C(0,-30,0)\\ G6B-09\S1(F,Z,8)\C((0,0,5),1)\ [C(0,5,0),1)]\ S2(F,XY,BB0,4)\M(30,-15,-5)

G8-02

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\C(0,0,20) [C(0,0,20)]\\G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,5)

G8-09

G6B-11\AP(XZ,BB4,4,100º)\ AP(XY,BB0,5,360º)\\ G6B-09\S1(F,Z,8)\C((0,0,5),1)\ [C(0,5,0),1)]\ S1(F,Z,10)[M(0,0,-30)]

G8-10

Population 08

G8-03

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\C(-30,0,0)\\ G6B-09\S1(F,Z,8)\C((0,0,5),1)\ AP(XY,BB0,6,360º)\ S2(F,XZ,BB1,3)\R3(F,Z,BB2,-90º)

G6B-11\AP(XZ,BB4,4,100º)\ MR(T,XZ,BB3)\\G6B-08\ R3(F,Y,BB4,90º)\M(0,0,-22)\ R3(F,X,BB3,90º)\ S2(F,YZ,BB2,2)

G8-11

G8-04

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\ S1(F,Y,0.5)\ AP(ZY,BB6,5,180º)\\G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\ AP(XZ,BB1,4,-90º)

G6B-11\AP(XZ,BB4,4,100º)\ AP(XZ,BB4,6,180º)\\ G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\ S1(F,Z,5)

G8-12

G8-05

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\ MR(T,XY,BB0)\[M(0,0,20)]\\G6B-09\ S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\ S2(F,XY,BB0,5)\M(30,0,-60)

G6B-11\ AP(XZ,BB4,4,100º)\ MR(T,YZ,BB0)\\G6B-09\ S1(F,Z,8)\C((0,0,5),1)\ [C(0,5,0),1)]\ S2(F,XY,BB0,3)

G8-13

G6B-11\ AP(XZ,BB4,4,100º)\C(0,0,40)\\ G6B-09\S1(F,Z,8)\C((0,0,5),1)\ [C(0,5,0),1)]\S2(F,XY,BB0,3)

G8-06

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\ AP(XY,BB7,8,270º)\MR(T,XY,BB0)\ [M(0,0,50)]\\G6B-09\ S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\ S1(F,Z,10)\M(0,50,0)

G8-14

G6B-11\AP(XZ,BB4,4,100º)\ AP(XY,BB1,5,360º)\\G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\ S2(F,XZ,BB0,2)

G8-07

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200º)]\R3(F,X,BB7,90º)\ MR(T,XZ,BB0)[M(0,30,0)]\\G6B-08\ R3(F,Y,BB4,90º)\ M(0,0,-22)\M(40,35,0)\S2(F,YZ,BB1,2)\ AP(XY,BB0,3,360º)

G8-15

G6B-11\AP(XZ,BB4,4,100º)\ AP(XZ,BB0,8,120º)\\G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\ S1(F,Z,3)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

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Sequence 02

Population 08

INDIVIDUAL # GENOME G8-01 G8-02 G8-03 G8-04 G8-05 G8-06 G8-07 G8-08 G8-09 G8-10 G8-11 G8-12 G8-13 G8-14 G8-15

V +05 +05 +06 +05 +05 +05 +06 +05 +05 +06 +06 +06 +05 +05 +06

G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\[AP(XY,BB0,6,360º)\\G6B-6\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\[S2(F,XZ,BB0,5)]\M(-20,0,-20) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\C(0,0,20)[C(0,0,20)]\\G6B-17\R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,5) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\C(-30,0,0)\\G6B-16\S1(F,Z,8)\C((0,0,5),1)\AP(XY,BB0,6,360º)\S2(F,XZ,BB1,3)\R3(F,Z,BB2,-90º) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\S1(F,Y,0.5)\AP(ZY,BB6,5,180º)\\G6B-17\R3(F,Y,BB4,90)\M(0,0,-22)\AP(XZ,BB1,4,-90º) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\MR(T,XY,BB0)\[M(0,0,20)]\\G6B-16\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\S2(F,XY,BB0,5)\M(30,0,-60) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\AP(XY,BB7,8,270º)\MR(T,XY,BB0)\[M(0,0,50)]\\G6B-16\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\S1(F,Z,10)\M(0,50,0) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\R3(F,X,BB7,90º)\MR(T,XZ,BB0)[M(0,30,0)]\\G6B-17\R3(F,Y,BB4,90º)\M(0,0,-22)\M(40,35,0)\S2(F,YZ,BB1,2)\AP(XY,BB0,3,360º) G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\C(0,-30,0)\\ G6B-16\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\S2(F,XY,BB0,4)\M(30,-15,-5) G6B-20\AP(XZ,BB4,4,100º)\AP(XY,BB0,5,360º)\\G6B-16\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\S1(F,Z,10)[M(0,0,-30)] G6B-20\AP(XZ,BB4,4,100º)\MR(T,XZ,BB3)\\G6B-17\R3(F,Y,BB4,90º)\M(0,0,-22)\R3(F,X,BB3,90º)\S2(F,YZ,BB2,2) G6B-20\AP(XZ,BB4,4,100º)\AP(XZ,BB4,6,180º)\\G6B-17\R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,5) G6B-20\AP(XZ,BB4,4,100º)\MR(T,YZ,BB0)\\G6B-16\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\S2(F,XY,BB0,3) G6B-20\AP(XZ,BB4,4,100º)\C(0,0,40)\\G6B-16\S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\S2(F,XY,BB0,3) G6B-20\AP(XZ,BB4,4,100º)\AP(XY,BB1,5,360º)\\G6B-17\R3(F,Y,BB4,90)\M(0,0,-22)\S2(F,XZ,BB0,2) G6B-20\AP(XZ,BB4,4,100º)\AP(XZ,BB0,8,120º)\\G6B-17\R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,3)

AFINDIVIDUAL V/AF # 4.96E+03 4.45E+03 1.41E+04 1.18E+04 1.17E+04 6.86E+03 3.37E+04 2.23E+03 4.08E+03 7.85E+03 8.80E+03 1.13E+04 4.88E+03 3.65E+03 3.43E+04

V/AF

N. DISTRIBUTION

1062 3.06E+05 1262 2.75E+05 377 1.08E+06 780 9.51E+05 1480 9.41E+05 882 5.59E+05 197 3.26E+06 13 102 2.27E+05 15 120 4.91E+05 137 5 1.07E+06 153 4 1.35E+06 175 9 1.98E+06 11 201 9.81E+05 201 2 7.35E+05 201 6 6.92E+06

4.96E+03 4.45E+03 1.41E+04 1.18E+04 1.17E+04 6.86E+03 3.37E+04 2.23E+03 4.08E+03 7.85E+03 8.80E+03 1.13E+04 4.88E+03 3.65E+03 3.43E+04

62 62 77 80 80 82 97 102 120 137 153 175 201 201 201

3.92E-03 3.94E-03 5.23E-03 5.56E-03 5.56E-03 5.66E-03 6.78E-03 7.08E-03 7.62E-03 7.33E-03 6.39E-03 4.56E-03 2.43E-03 2.43E-03 2.41E-03

MEAN 122 S.DEVIATION52

122 52

Population 08, is the result of the hierarchical assemblies of the 2 fittest individuals selected from population 07 and 1 or 2 operations added to each part of the genome. This manipulation allowed to stabilize even more the curve and now the values of the individuals ranked according to the environmental pressure is closer to the mean.

N. DISTRIBUTION

9.00E-03 8.00E-03 7.00E-03 6.00E-03 5.00E-03 4.00E-03 3.00E-03 2.00E-03

3.92E-03 3.94E-03 5.23E-03 5.56E-03 5.56E-03 5.66E-03 6.78E-03 7.08E-03 7.62E-03 7.33E-03 6.39E-03 4.56E-03 2.43E-03 2.43E-03 2.41E-03

1.00E-03 0.00E+00 0.00E+00

5.00E+01

1.00E+02

1.50E+02

2.00E+02

2.50E+02

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Sequence 02

Based in the ratio between volume and density factor we selected the 6 fittest individuals.

G8-02

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200ยบ)]\C(0,0,20) [C(0,0,20)]\\G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,5)

G8-04

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200ยบ)]\ S1(F,Y,0.5)\ AP(ZY,BB6,5,180ยบ)\\G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\ AP(XZ,BB1,4,-90ยบ)

Population 08

G8-05

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200ยบ)]\ MR(T,XY,BB0)\[M(0,0,20)]\\G6B-09\ S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\ S2(F,XY,BB0,5)\M(30,0,-60)

G8-06

G6B-11\M(0,0,60)\ [AP(XZ,BB5,8,200ยบ)]\ AP(XY,BB7,8,270ยบ)\MR(T,XY,BB0)\ [M(0,0,50)]\\G6B-09\ S1(F,Z,8)\C((0,0,5),1)\[C(0,5,0),1)]\ S1(F,Z,10)\M(0,50,0)

G8-09

G6B-11\AP(XZ,BB4,4,100ยบ)\ AP(XY,BB0,5,360ยบ)\\ G6B-09\S1(F,Z,8)\C((0,0,5),1)\ [C(0,5,0),1)]\ S1(F,Z,10)[M(0,0,-30)]

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G8-11

G6B-11\AP(XZ,BB4,4,100ยบ)\ AP(XZ,BB4,6,180ยบ)\\ G6B-08\ R3(F,Y,BB4,90)\M(0,0,-22)\ S1(F,Z,5)

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Sequence 02 Logic diagram

POPULATION 06B

G6A-02

G6B-02

G6A-03

G6A-04

G6A-05

G6A-05 G6A-06

G6B-04

G6A-07

G6B-05 G6B-03

1º HALF

G2-03

G6A-06

2º HALF

G2-03

G6A-07 G6A-08 CROSS BREEDING STRATEGY

G6A-09

1º HALF

G5-11

2º HALF

G5-11

1º HALF

G3-09

2º HALF

G3-09

G6A-10 G6A-11 G6A-12

SEXUAL REPRODUCTION

G6B-03 G6B-01

G6A-08 G6A-09

G6B-06 G6B-11

G6A-10 G6B-02

G6A-11 G6A-12

G6B-07

G6A-13

G6A-14

G6A-15

G6A-16

G6B-08

G6A-17

G6B-09

G6A-18

G6B-10

G6A-19

G6A-20

G6B-08 G6B-09

G6B-11

SEXUAL REPRODUCTION

6 SURVIVORS

2 FITTEST ACCORDING TO STABILITY FACTOR

FINAL EVALUATION FITTEST INDIVIDUALS OF POP 8

G7-01

G8-01

G7-02

G8-02

G7-03

G7-04

G7-05

G7-06 G7-07 G7-08 G7-09 G7-10 G7-11

G7-06

G7-11

G7-07

G7-05

G7-08

G7-13

G7-09

G7-15

G7-10

G7-09

G7-15 G6B-09\S1 \ C \ C \\ G6B-08 \ R \ M

G7-14 G6B-11 \ M \ AP \\ G6B-11 \ AP

G7-11

G7-12

G7-13

G7-14

G7-15

G7-14

HIERARCHICAL ASSEMBLY OF PARTS OF 2 FITTEST SURVIVORS + 1 OR 2 OPERATION PER PART

G6A-02

POPULATION 08

STABILITY FACTOR

G6B-01

Individuals below the mean value will be killed.

G3-05

G6A-01

DUPLICATION

2º HALF

G6A-01

DELETION

G3-05

KILLING STRATEGY ACCORDING TO THE ENVIRONMENTAL PRESSURE

LOWEST LEVEL INDIVIDUALS

MUTATIONS

1º HALF

POPULATION 07

ENVIRONMENTAL PRESSURE

POPULATION 06A

CREATION OF HIERARCHICAL ASSEMBLIES

PRIMITIVE

G8-03 G8-04 G8-05 G8-06

G8-02

G8-07

G8-04

G8-08

G8-05

G8-09

G8-06

G8-10

G8-09

G8-11

G8-12 G8-13 G8-14 G8-15

SEXUAL REPRODUCTION

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Genome Embryological Development Evolutionary Stage

Sequence 03

G6B-20\M(0,0,60)\[AP(XZ,BB5,8,200º)]\C(0,0,20)[C(0,0,20)]\\G6B-17\R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,5) M(0,0,60)\[AP(XZ,BB5,8,200º)]\C(0,0,20)[C(0,0,20)] G6B-20

R3(F,Y,BB4,90)\M(0,0,-22)\S1(F,Z,5) G6B-17

Body Plan

RP6

RP7

RP10 RP2

RP5

RP9 RP3

RP4 RP8 RP1

the populations of sequence 3 are generated by a script. The reference points of each operation are referring to the vertexes of the bounding box of the paraboloid in order to avoid the necessity to work with absolute values, which ,in previous generations resulted in disconnection of parts of the individual. In order to create hierarchies population 9 is created as small assemblies of paraboloids. Four operation are applied to create one assembly. The assembles are then evaluated for stability. The assumption was that a stable parent will create stable offsprings. OPERATIONS: M MOVE C COPY A ARRAY POLAR S SCALE R ROTATE 3D N MIRROR

(vector start point, vector end point) (vector start point, vector end point) (angle, rot. axis start point, rot. axis end point, rot. centre) (X factor, Y factor, Z factor) (angle, rot. axis start point, rot. axis end point, rot. centre, copy) (rot. centre, normal start point, normal end point)

Fitness Criteria S

BREEDING STRATEGY The breeding strategy was based on the fittest individuals from the previous populations

Exposure ratio = S V V

REFERENCE POINT

MUTATION STRATEGY The mutation was restricted to two operations: -Duplication -Deletion -Insertion -Transposition ENVIRONMENTAL PRESSURES The individuals are trying to get the more energy (Exposure) as possible. Therefore they are expanding their surface area.

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Sequence 03

Logic diagram for Sequence 03 In order to create hierarchies population 9 is created as small assemblies of paraboloids. Four operation are applied to create one assembly. The assembles are then evaluated for stability. The assumption was that a stable parent will create stable offsprings.

Chart of iterations between Evolution and Embryological Development Evolution

Embryological Development

Killing Strategy

Scripted Breeding strategies

Scripted Environmental pressure Mutations

Stability

Fitness Criteria

Sequence 03 Population 09

Primitive

4 random operations

Stability Factor

Population 10

Survaivors of pop 9-small assembly

2-8 random operations

Disconnected Geometry

Exposure ratio

Population 11

Crossbreeding of 4 fittest individuals from pop 10

2-8 random operations

Disconnected Geometry

Exposure ratio

Population 9 population of small assemblies

Population 10 script generated genomes act on those small assemblies

Population 11 Fittest of population 10 are cross bread

Primitive

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Sequence 03

Population 09 was started asexually by applying a script that selected 4 operations randomly chosen between 6 basic rhino operations.

G9-01

C(9,7)\R(259,3,1,3,F)\M(9,3)\ R(325,1,4,5,F)\C(9,7)\ R(259,3,1,3,F)\M(9,3)

G9-09

M(9,7)\N(8,2,9,)\ A(152,4,8,4,3)\M(9,0)

G9-02

N(5,4,8)\M(9,6)\A(257,1,6,1,6)\ R(275,1,4,8,T)

G9-10

R(345,2,5,6,F)\N(1,2,1,)\ C(9,5)\S(1,1.3,1.3)

G9-03

N(2,7,1)\S(1.4,1.4,1.4)\ C(9,6)\C(9,6)

G9-11

S(0.9,0.9,1)\A(346,5,3,8,1)\ S(0.7,0.7,1)\R(052,4,5,1,T)

Population 09

G9-04

M(9,7)\M(9,10)\ S(1,1.3,1.3)\M(9,7)

G9-12

N(4,9,7)\N(6,9,1)\ C(9,2)\N(4,9,6)

G9-05

C(9,7)\C(9,10)\M(9,10)\C(9,7)

G9-13

N(1,8,1,)\S(1.8,1,1.8)\ A(359,9,7,1,1)\C(9,6)

G9-06

C(9,7)\N(2,7,4)\ S(1.3,1.3,1.3)\S(1.7,1,1.7)

G9-14

N(3,4,6)\C(9,3)\ N(5,1,4)\C(9,6)

G9-07

C(9,7)\R(295,4,2,5,F)\ C(9,3)\A(107,3,0,0,4)

G9-15

M(9,7)\C(9,10)\N(1,5,9)\ S(1,1,1.9)

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G9-08

N(7,0,2,)\S(1,1.9,1)\ S(1.3,1,1.3)\A(247,2,4,5,6)

G9-16

N(4,0,5)\R(0,42,7,9,1,T)\ R(159,4,7,9,F)\N(5,4,1)

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Sequence 03

Population 09

As can be seen from the graph, the distribution of Population 09 is totally unbalanced because of the presence of individual G9-02 whose Stability Factor is approximately 100 times bigger than the values related to the other individuals. As a result, it is possible to see in the first table that the Standard Deviation is higher than the ones in the other populations.

INDIVIDUAL # GENOME G9-01 G9-02 G9-03 G9-04 G9-05 G9-06 G9-07 G9-08 G9-09 G9-10 G9-11 G9-12 G9-13 G9-14 G9-15 G9-16

9.49 5.68 1.30 9.02 6.77 1.23 4.79 9.45 0.89 8.67 8.35 3.69 5.08 3.55 3.02 5.61

C(9,7)\R(259,3,1,3,F)\M(9,3)\R(325,1,4,5,F)\C(9,7)\R(259,3,1,3,F)\M(9,3)\R(325,1,4,5,T) N(5,4,8)\M(9,6)\A(257,1,6,1,6)\R(275,1,4,8,T) N(2,7,1)\S(1.4,1.4,1.4)\C(9,6)\C(9,6) M(9,7)\M(9,10)\S(1,1.3,1.3)\M(9,7) C(9,7)\C(9,10)\M(9,10)\C(9,7) C(9,7)\N(2,7,4)\S(1.3,1.3,1.3)\S(1.7,1,1.7) C(9,7)\R(295,4,2,5,F)\C(9,3)\A(107,3,0,0,4) N(7,0,2,)\S(1,1.9,1)\S(1.3,1,1.3)\A(247,2,4,5,6) M(9,7)\N(8,2,9,)\A(152,4,8,4,3)\M(9,0) R(345,2,5,6,F)\N(1,2,1,)\C(9,5)\S(1,1.3,1.3) S(0.9,0.9,1)\A(346,5,3,8,1)\S(0.7,0.7,1)\R(052,4,5,1,T) N(4,9,7)\N(6,9,1)\C(9,2)\N(4,9,6) N(1,8,1,)\S(1.8,1,1.8)\A(359,9,7,1,1)\C(9,6) N(3,4,6)\C(9,3)\N(5,1,4)\C(9,6) M(9,7)\C(9,10)\N(1,5,9)\ N(4,0,5)\R(0,42,7,9,1,T)\R(159,4,7,9,F)\N(5,4,1)

bINDIVIDUAL FS = a/b # 0.76 0.24 1.64 1.70 3.58 3.41 1.71 3.60 5.34 4.52 4.56 4.99 6.56 3.58 4.97 0.06

-25.64 1 -23.67 5 -6.89 9 -5.31 10 -4.68 8 -3.29 7 -2.80 16 -2.63 2 -2.04 14 -1.92 12 -1.83 15 0.74 4 13 0.77 11 0.99 2.62 6 96.72 3

MEAN 1.32 S.DEVIATION 26.69

FS = a/b

N. DISTRIBUTION

19.49 5.68 11.30 9.02 16.77 11.23 4.79 9.45 10.89 8.67 8.35 3.69 5.08 3.55 13.02 5.61

0.76 0.24 1.64 1.70 3.58 3.41 1.71 3.60 5.34 4.52 4.56 4.99 6.56 3.58 4.97 0.06

-25.64 -23.67 -6.89 -5.31 -4.68 -3.29 -2.80 -2.63 -2.04 -1.92 -1.83 0.74 0.77 0.99 2.62 96.72

8.974E-03 9.642E-03 1.425E-02 1.449E-02 1.457E-02 1.472E-02 1.477E-02 1.478E-02 1.483E-02 1.484E-02 1.484E-02 1.494E-02 1.494E-02 1.494E-02 1.493E-02 2.517E-05

N. DISTRIBUTION

0.02

8.974E-03 9.642E-03 1.425E-02 0.01 1.449E-02 0.01 1.457E-02 1.472E-02 0.01 1.477E-02 1.478E-02 0.01 1.483E-02 1.484E-02 0.01 1.484E-02 0.00 1.494E-02 1.494E-02 0.00 1.494E-02 1.493E-02 0.00 0.00 2.517E-05 20.00 0.02

40.00

60.00

80.00

100.00

120.00

1.32 26.69

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Sequence 03

In Population 10 a sequence of 2 to 8 random script generated operations (chosen from a catalogue of operations) acts on those assemblies. Environmental Pressure forces the population to grow preferably in the vertical direction. However the environmental pressure is relatively weak, and the vertical growth is only incorporated in two of the six possible operation, namely move and copy.

G10-01

G9-01\C(9,3)\C(9,7)\ R(079,2,7,1,F)\ S(2.4,1,1)\N(2,3,6)

G10-07

G9-11\C(9,3)\ A(014,2,1,1,2)\N(1,0,4)\ C(9,5)\N(2,7,1,)\S(1,1,2)\ N(8,9,1,)\S(0.5,0.5,1)

G10-02

G10-03

G9-01\C(9,3)\N(1,9,2)\ S(2.3,1,1)\S(0.9,0.9,1)\ A(204,3,5,5,3)\ S(2.1,2.1,2.1)\N(9,5,6)

G10-08

G9-11\R(130,2,1,2,F)\ S(1.7,1,1.7)\A(123,0,3,1,8)\ R(162,3,9,5,T)

Population 10

G10-04

G9-06\A(263,6,1,2,7)\ C(9,7)\S(1,2.1,1)\ S(1,2.5,1)\A(329,1,8,1,9)\ R(325,9,0,1,T)\ C(9,6)\N(6,9,1)

G10-09

G9-11\M(9,3)\ A(244,6,8,5,5)\C(9,2)

G10-10

G9-11\R(140,8,4,7,T)\ A(221,7,9,1,6)\C(9,0)\ A(122,5,1,3,6)\C(9,3)\C(9,5)\ N(3,2,6,)\R(092,2,6,3,F)\ R(032,6,8,1,T)

G10-05

G9-06\M(9,7)\C(9,3)\ R(021,8,6,8,T)\S(0.9,0.9,0.9)\ S(1.7,1,1)\C(9,7)\C(9,4)\ C(9,)\S(1.6,1,1.6)

G10-11

G9-13\R(00,5,9,1,F)\C(9,7)\ C(9,3)\C(9,)\A(155,2,7,7,8)\ S(2.3,2.3,2.3)\C(9,6)\ R(162,1,7,1,T)\C(9,0)

G10-12

G9-06\M(9,6)\R(251,1,8,9,T)\ A(118,1,8,7,3)\M(9,0)\ R(055,8,4,3,F)\ A(116,2,1,2,9)\M(9,0)

G9-13\C(9,7)\C(9,3)\ M(9,4)\R(261,1,8,1,F)\ R(086,2,4,5,F)\N(0,1,5)\ A(149,5,7,1,9)\M(9,7)

G10-13

G9-13\A(328,6,1,4,1)\ A(356,6,7,0,9)\N(1,0,8)

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G10-06

G9-06\S(2.5,1,1)\M(9,6)\ R(258,9,7,1,F)\R(046,0,7,7,F)\ N(7,1,1,)\A(127,6,9,6,6)\C(9,6)\ S(1,1.9,1)\S(0.9,0.9,0.9)

G10-14

G9-13\A(184,3,8,0,4)\C(9,7)\ R(359,3,4,8,T)\A(131,7,6,3,9)\ C(9,5)\S(2.4,1,2.4)

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Sequence 03

Population 10

The individuals of Population 10 were ranked according to the Exposure Ratio (S/V). As can be seen from the graph, the distribution of Population 10 approximates the bell curve. In fact, even if there is a monster (G10-08), the standard deviation of Population 10 is smaller than 1.00 and the Exposure Ratios of the individuals are generally close to the mean value.

INDIVIDUAL # GENOME G9-01 G9-02 G9-03 G9-04 G9-05 G9-06 G9-07 G9-08 G9-09 G9-10 G9-11 G9-12 G9-13 G9-14 G9-15 G9-16

1134.00 1348.00 1239.00 1073.00 3287.00 3392.00 2362.00 2337.00 2515.00 4180.00 7449.00 6668.00 5407.00

INDIVIDUAL V FS = S/V # 5870.00 6259.00 5732.00 4572.00 8749.00 7635.00 4932.00 4747.00 4572.00 3584.00 4568.00 3162.00 1554.00

0.19 5 0.21 12 0.22 4 0.23 13 0.37 1 0.44 10 0.48 7 0.49 9 0.55 14 1.17 11 1.63 3 2.11 2 3.48 8

MEAN 0.89 S.DEVIATION 0.98

FS = S/V

N. DISTRIBUTION

1134.00 1348.00 1239.00 1073.00 3287.00 3392.00 2362.00 2337.00 2515.00 4180.00 7449.00 6668.00 5407.00

5870.00 6259.00 5732.00 4572.00 8749.00 7635.00 4932.00 4747.00 4572.00 3584.00 4568.00 3162.00 1554.00

0.19 0.21 0.22 0.23 0.37 0.44 0.48 0.49 0.55 1.17 1.63 2.11 3.48

3.151E-01 3.196E-01 3.219E-01 3.241E-01 3.531E-01 3.657E-01 3.723E-01 3.739E-01 3.826E-01 3.900E-01 3.058E-01 1.878E-01 1.255E-02

0.89 0.98

N. DISTRIBUTION 0.45

0.40 0.35 0.30 0.25 0.20 0.15 0.10

3.151E-01 3.196E-01 3.219E-01 3.241E-01 3.531E-01 3.657E-01 3.723E-01 3.739E-01 3.826E-01 3.900E-01 3.058E-01 1.878E-01 1.255E-02

0.05 0.00 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 03

Population ten is evaluated for the best Surface area / Volume Ratio. The fittest individuals are cross-bread in order to generate population 11.

Population 11

G10-02

CROSSBREEDING G11-01 G10-08

MUTATIONS G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\

G10-02 G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)

G10-03

G10-08

G10-14

FINAL GENOME G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\G9-01\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\S(2.1,2.1,2.1)\N(9,5,6)

G10-14

G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\ G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)

G9-11\A(123,0,3,1,8)\R(162,3,9,5,T)\G9-13\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)

G10-03

G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,)\N(6,9,1)

G9-11\R(130,2,1,2,F)\R(162,3,9,5,T)\G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)

G10-02

G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\ G9-01\C(9,3)\N(1,9,2)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)

G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\G9-01\C(9,3)\N(1,9,2)\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)

G11-05 G10-08

G10-14

G11-06 G10-08

G10-03

G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\ G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\ G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G11-07 G10-02

G10-08 G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\ G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)

G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\N(9,5,6)\G9-11\A(123,0,3,1,8)\R(162,3,9,5,T)

G11-08 G10-02

G10-14

G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\ G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\

G9-01\C(9,3)\S(0.9,0.9,1)\A(204,3,5,5,3)\C(9,7)\R(359,3,4,8,T)\S(2.1,2.1,2.1)\N(9,5,6)\G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\

G10-03

G9-01\C(9,3)\N(1,9,2)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G9-01\C(9,3)\N(1,9,2)\S(0.9,0.9,1)\A(204,3,5,5,3)\G9-06\A(263,6,1,2,7)\C(9,7)\S(2.1,2.1,2.1)\N(9,5,6)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)

G10-08

G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\ G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)

G9-01\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\G9-11\R(130,2,1,2,F)

G10-14

G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\ G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\

G9-01\S(2.3,1,1)\S(0.9,0.9,1)\N(9,5,6)\G9-13\A(184,3,8,0,4)\A(131,7,6,3,9)

G11-12 G10-02

G10-03

G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G9-01\C(9,3)\N(1,9,2)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\G9-06\C(9,3)\N(1,9,2)\S(2.3,1,1)\A(263,6,1,2,7)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G11-13 G10-14

G10-08 G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\

G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\G9-11\A(123,0,3,1,8)\R(162,3,9,5,T)

G11-14 G10-14

G10-02

G9-13\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\G9-01\C(9,3)\N(1,9,2,)\S(2.1,2.1,2.1)\N(9,5,6)

G11-02 G10-08 G11-03 G10-08 G11-04 G10-08

G11-09 G10-02 G11-10 G10-02 G11-11 G10-02

G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T) G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\ G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6) G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G11-15 G10-14

G10-03

G11-16 G10-14

G10-08 G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\ G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)

G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\ G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6) G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G9-11\R(130,2,1,2,F)\A(184,3,8,0,4)\C(9,7)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)\G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,5) G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\A(329,1,8,1,9)\R(325,9,0,1,T)\G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\C(9,5)\N(6,9,1)

G9-13\A(131,7,6,3,9)\C(9,5)\S(2.4,1,2.4)\G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\C(9,5)\N(6,9,1)\R(325,9,0,1,T) G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\G9-11\A(184,3,8,0,4)\S(1.7,1,1.7)\A(123,0,3,1,8)

G11-17 G10-14

G10-02

G11-18 G10-14

G10-03

G11-19 G10-03

G10-08 G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\ G9-06\A(329,1,8,1,9)\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\G9-11\R(162,3,9,5,T) G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)

G11-20 G10-03

G10-02 G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\ G9-06\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(1,9,2)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\N(6,9,1)\G9-01\C(9,3)\S(2.1,2.1,2.1)\N(9,5,6) G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)

G11-21 G10-03

G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\ G10-14 G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,)\S(2.4,1,2.4)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\A(263,6,1,2,7)\C(9,7)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)

G11-22 G10-03

G10-08 G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\ G9-06\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,7)\G9-11\S(1,2.1,1)\A(123,0,3,1,8)\R(162,3,9,5,T) G9-11\R(130,2,1,2,F)\S(1.7,1,1.7)\A(123,0,3,1,8)\R(162,3,9,5,T)

G11-23 G10-03

G10-02 G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\ G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\R(325,9,0,1,T)\G9-01\C(9,3)\N(1,9,2,)\S(1,2.5,1)\A(329,1,8,1,9)\S(2.3,1,1)\N(9,5,6) G9-01\C(9,3)\N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6)

G11-24 G10-03

G10-14 G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\C(9,)\S(2.4,1,2.4)\

G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\

G9-13\R(359,3,4,8,T)\A(184,3,8,0,4)\C(9,7)\S(2.4,1,2.4)\G9-01\A(204,3,5,5,3)\S(2.1,2.1,2.1)\N(9,5,6) G9-13\G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\C(9,7)\R(359,3,4,8,T)\A(131,7,6,3,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)

G9-06\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,5)\N(6,9,1)\G9-13\A(184,3,8,0,4)\C(9,7)\R(359,3,4,8,T)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\R(325,9,0,1,T)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 03

the individuals of sequence three are very complicated yet not complex. This is mainly due to the lack of a differentiated body-plan and a homeobox witch acts on the the body plan. In consequence two more generations are created.

G11-01

R(130,2,1,2,F)\ S(1.7,1,1.7)\ A(123,0,3,1,8)\ N(1,9,2,)\S(2.3,1,1)\ S(2.1,2.1,2.1)\N(9,5,6)

G11-08

C(9,3)\S(0.9,0.9,1)\ A(204,3,5,5,3)\C(9,7)\ R(359,3,4,8,T)\S(2.1,2.1,2.1)\ N(9,5,6,)\A(184,3,8,0,4)\C(9,7)\ R(359,3,4,8,T)\A(131,7,6,3,9)\ C(9,)\S(2.4,1,2.4)

G11-02

A(123,0,3,1,8)\R(162,3,9,5,T)\ R(359,3,4,8,T)\A(131,7,6,3,9)\ C(9,)\S(2.4,1,2.4)

G11-09

C(9,3)\N(1,9,2,)\ S(2.3,1,1)\S(0.9,0.9,1)\ A(204,3,5,5,3)\A(263,6,1,2,7)\ C(9,7)\S(2.1,2.1,2.1)\ N(9,5,6,)\S(1,2.1,1)\ S(1,2.5,1)\A(329,1,8,1,9)

Population 11

G11-03

R(130,2,1,2,F)\ R(162,3,9,5,T)\ A(263,6,1,2,7)\ C(9,7)\S(1,2.1,1)\ S(1,2.5,1)\A(329,1,8,1,9)

G11-10

A(204,3,5,5,3)\ S(2.1,2.1,2.1)\N(9,5,6,)\ R(130,2,1,2,F)

G11-04

R(130,2,1,2,F)\ S(1.7,1,1.7)\A(123,0,3,1,8)\ R(162,3,9,5,T)\C(9,3)\ N(1,9,2,)\R(130,2,1,2,F)\ S(1.7,1,1.7)\ A(123,0,3,1,8)\S(2.3,1,1)\ S(0.9,0.9,1)\A(204,3,5,5,3)

G11-11

S(2.3,1,1)\S(0.9,0.9,1)\ N(9,5,6,)\A(184,3,8,0,4)\ A(131,7,6,3,9)\C(9,5)

G11-05

R(130,2,1,2,F)\ A(184,3,8,0,4)\C(9,7)\ S(1.7,1,1.7)\A(123,0,3,1,8)\ R(162,3,9,5,T)\A(184,3,8,0,4)\ C(9,7)\R(359,3,4,8,T)\ A(131,7,6,3,9)\C(9,)

G11-12

G11-06

R(130,2,1,2,F)\S(1.7,1,1.7)\ A(123,0,3,1,8)\A(329,1,8,1,9)\ R(325,9,0,1,T)\A(263,6,1,2,7)\C(9,7)\ S(1,2.1,1)\S(1,2.5,1)\C(9,4)\N(6,9,1,)

C(9,3)\N(1,9,2,)\S(2.3,1,1)\ S(0.9,0.9,1)\A(204,3,5,5,3)\ S(2.1,2.1,2.1)\C(9,3)\ N(1,9,2,)\S(2.3,1,1)\ N(9,5,6,)\A(263,6,1,2,7)\ A(329,1,8,1,9)\R(325,9,0,1,T)\ C(9,)\N(6,9,1,)

G11-07

C(9,3)\N(1,9,2,)\ S(2.3,1,1)\N(9,5,6,)\ A(123,0,3,1,8)\ R(162,3,9,5,T)

G11-13

A(184,3,8,0,4)\C(9,7)\ R(359,3,4,8,T)\A(131,7,6,3,9)\ A(123,0,3,1,8)\R(162,3,9,5,T)

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In Generation 11 a sequence of 2 to 8 random script generated operations ( chosen from a catalogue of operations) acts on those assemblies. Environmental Pressure forces the population to grow preferably in the vertical direction.

G11-14

G11-20

A(329,1,8,1,9)\R(325,9,0,1,T)\C(9,)\ N(1,9,2,)\S(2.3,1,1)\S(0.9,0.9,1)\ A(204,3,5,5,3)\N(6,9,1,)\C(9,3)\ S(2.1,2.1,2.1)\N(9,5,6,)

G11-16

G11-15

A(131,7,6,3,9)\C(9,)\ S(2.4,1,2.4)\C(9,3)\N(1,9,2,)\ S(2.1,2.1,2.1)\N(9,5,6,)

A(184,3,8,0,4)\C(9,7)\ R(359,3,4,8,T)\A(184,3,8,0,4)\ S(1.7,1,1.7)\A(123,0,3,1,8)

A(131,7,6,3,9)\ C(9,)\S(2.4,1,2.4)\ A(263,6,1,2,7)\C(9,7)\ S(1,2.1,1)\S(1,2.5,1)\ C(9,)\N(6,9,1,)\C(9,7)\ R(359,3,4,8,T)

G11-21

A(263,6,1,2,7)\C(9,7)\ S(1,2.1,1)\A(263,6,1,2,7)\ C(9,7)\R(325,9,0,1,T)\ C(9,)\N(6,9,1,)\ A(184,3,8,0,4)\C(9,7)\ R(359,3,4,8,T)

Sequence 03

However the environmental pressure is relatively weak, and the vertical growth is only incorporated in two of the six possible operation, namely move and copy. Population ten is evaluated for the best Surface area / Volume Ratio. The fittest individuals are cross-bread in order to generate population 11.

G11-22

C(9,7)\S(1,2.1,1)\S(1,2.5,1)\ A(329,1,8,1,9)\R(325,9,0,1,T)\ C(9,7)\S(1,2.1,1)\ A(123,0,3,1,8)\R(162,3,9,5,T)

G11-17

R(359,3,4,8,T)\ A(184,3,8,0,4)\ C(9,7)\S(2.4,1,2.4)\ A(204,3,5,5,3)\ S(2.1,2.1,2.1)\N(9,5,6,)

G11-23

Population 11

G11-19

G11-18

A(329,1,8,1,9)\A(263,6,1,2,7)\ C(9,7)\S(1,2.1,1)\S(1,2.5,1)\ A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\ R(325,9,0,1,T)\C(9,)\N(6,9,1,)\ R(162,3,9,5,T)

A(263,6,1,2,7)\C(9,7)\ S(1,2.1,1)\C(9,7)\ R(359,3,4,8,T)\ A(131,7,6,3,9)\ R(325,9,0,1,T)\C(9,)\N(6,9,1,)

A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\ R(325,9,0,1,T)\C(9,3)\N(1,9,2,)\ S(1,2.5,1)\A(329,1,8,1,9)\ S(2.3,1,1)\N(9,5,6,)

G11-24

A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\A(329,1,8,1,9)\ R(325,9,0,1,T)\C(9,)\N(6,9,1,)\A(184,3,8,0,4)\C(9,7)\ R(359,3,4,8,T)\A(263,6,1,2,7)\C(9,7)\S(1,2.1,1)\S(1,2.5,1)\ A(329,1,8,1,9)\R(325,9,0,1,T)

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Sequence 03 Population 11

2765 1175 1233 1837 2186 1431 1495 1265 5818 6362 9608 2500 2903 9937 2601 5525 3691 2370 8681 4379 9632 NULL NULL NULL

INDIVIDUAL V FS = S/V# 1683 8257 6835 7200 8158 4466 4278 1303 5496 5780 7591 1881 1979 6550 1637 3368 1769 1111 2792 1228 1028 NULL NULL NULL

0.028 0.14 12 0.181 0.266 0.274 0.325 0.353 0.97 15 1.06 17 1.10 14 1.27 22 1.33 20 1.47 21 1.52 19 1.59 18 1.64 24 2.09 16 2.13 13 3.117 3.572 9.379 NULL 10 NULL 11 NULL 23

MEAN 1.61 S.DEVIATION 2.02

FS = S/V

N. DISTRIBUTION

2765 1175 1233 1837 2186 1431 1495 1265 5818 6362 9608 2500 2903 9937 2601 5525 3691 2370 8681 4379 9632 NULL NULL NULL

1683 8257 6835 7200 8158 4466 4278 1303 5496 5780 7591 1881 1979 6550 1637 3368 1769 1111 2792 1228 1028 NULL NULL NULL

0.02 0.14 0.18 0.26 0.27 0.32 0.35 0.97 1.06 1.10 1.27 1.33 1.47 1.52 1.59 1.64 2.09 2.13 3.11 3.57 9.37 NULL NULL NULL

1.450E-01 1.517E-01 1.538E-01 1.581E-01 1.586E-01 1.612E-01 1.627E-01 1.879E-01 1.904E-01 1.914E-01 1.948E-01 1.956E-01 1.970E-01 1.973E-01 1.975E-01 1.975E-01 1.919E-01 1.910E-01 1.498E-01 1.232E-01 1.227E-04 NULL NULL NULL

After generating Population 11, the individuals were ranked according to the fitness criteria, the Exposure Ratio (S/V). As the graph clearly highlights, the population is roughly following the normal distribution. In particular, it is possible to realise that there is one individual (G11-09) that could be consider as a monster. In fact, its Exposure Ratio is respectively two times higher than the values related to closer individual in the ranking. In addition, some of the individuals have NULL values since they could not be evaluated and were killed.

N. DISTRIBUTION 0.25 1.450E-01 1.517E-01 1.538E-01 0.20 1.581E-01 1.586E-01 1.612E-01 0.15 1.627E-01 1.879E-01 1.904E-01 0.10 1.914E-01 1.948E-01 1.956E-01 0.05 1.970E-01 1.973E-01 1.975E-01 1.975E-01 0.00 1.919E-01 0.00 1.00 2.00 1.910E-01 1.498E-01 1.232E-01 1.227E-04 NULL NULL NULL

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00

1.61 2.02

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Sequence 03 Conclusions

POPULATION 09

COPY (C) MIRROR (N) ROTATE (R) ARRAY POLAR (A) SCALE (S) MOVE (M)

2-8 OPERATIONS RANDOMLY CHOSEN BETWEEN 6 BASIC RHINO OPERATIONS C \ R \M \ R

G9-01

N\M\A\R

G9-02

N \ S \C \ C

G9-03

M\M\S\M

G9-04

C \ C \M \ C

G9-05

C\N\S\S

G9-06

C\R\C\A

G9-07

N\S\S\A

G9-08

M\N\A\M

G9-09

R\N\C\S

G9-10

S\A\S\R

G9-11

N\N\C\N

G9-12

N\S\A\C

G9-13

N \ C \ N \ C G9-14

M\C\N\S

G9-15

N\R\R\N

G9-16

ASEXUAL REPRODUCTION

POPULATION 11 4 FITTEST OF POP. 10 ACCORDING TO THE EXPOSURE RATIO (S/V)

\C\C\R\S\N

G10-01

\C\N\S\S\A\S\N

G10-02

\ A \ C \ S \ S \ A \ R \ C\ N

G10-03

\M\C\R\S\S\C

G10-04

\M\R\A\M\R\A\M

G10-05

\S\M\R\R\N\A\C\S\S

G10-06

G10-02

\C\A\N\C\N\S\N\S

G10-07

G10-03

\R\S\A\R

G10-08

\M\A\C

G10-09

G10-14

\R\A\C\A\C\N\R\R

G10-10

\R\C\C\C\A\S\C\R\C

G10-11

\C\C\M\R\R\N\A\M

G10-12

\A\A\N

G10-13

\A\C\R\A\C\S

G10-14

ASEXUAL REPRODUCTION

The individuals of sequence three are very complicated yet not complex. This is mainly due to the lack of a differentiated body-plan and a homeobox witch acts on the the body plan. In consequence two more generations are created.

G11-01 G11-02 G11-03 G11-04 G11-05 G11-06 G11-07 G11-08 G11-09

CROSS BREEDING STRATEGY

Body Plan

SCRIPT APPLIED TO THE PRIMITIVE

4 OPERATIONS RANDOMLY CHOSEN BETWEEN 6 BASIC RHINO OPERATIONS

POPULATION 10

SCRIPT APPLIED TO THE SMALL ASSEMBLY OF POPULATION 09

PRIMITIVE

G11-10 G11-11 G11-12 G11-13 G11-14 G11-15 G11-16 G11-17 G11-18 G11-19 G11-20 G11-21 G11-22 G11-23 G11-24 SEXUAL REPRODUCTION

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Sequence 04 Body Plan

Number of operations

In order to add complexity and control the grow of the individuals, we reworked the bodyplan splitting the paraboloid into 4 sections.

A diferent number will be asigned to each part of the body plan.

Type of operation

Development sequence Order in the application of the selected operations on each section of the body plan.

C 4

2 6

N 1

RP6

Type of operation M(9,3) -> Move (Vector start point,Vector end point) C(4,6) -> Copy (Vector start point,Vector end point) A(263,6,1,2,7) -> ArrayPolar ( Angle, Rotation axis startpoint, Rotationaxis end point,Rotation point) S(1,2.5,1) -> Scale (X factor,Y factor, Z factor) R(325,9,0,1,T) -> Rotate( Angle, Rotation axis startpoint, Rotationaxis end point,Rotation point,Copy = true) N(1,9,2,) -> Mirror(Rotation point, Normal start point, Normal end point) RP

Reference Point

RP7 RP10 RP2

RP5

RP9 RP3

RP4 RP8

All Points are described by the index of the reference points of the body plan eg; M(7,3) -> Move from reference point number 7 to reference point number 3

RP1

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Sequence 04

For generation 12 a sequence of 2 to 8 random script generated operations are acting on each of the segments in order to create more differentiated individuals. Again the population is evaluated for their Surface/Volume ratio.

G12-01

M(9,3)\C(9,10)\M(9,5)\ S(0.7,0.7,0.7)\(162,6,1,3,3)\A(352,9,5,1,8)\ C(9,3)\S(0.6,1,0.6)\C(9,3)\S(1.6,1.6,1.6)\ A(349,6,6,2,7)\R(355,1,1,2,F)\ R(085,1,9,9,F)\R(159,8,3,7,F)\M(9,2)

G12-06

N(5,7,6)\A(089,1,4,8,5)\C(9,5)\ C(9,)\N(4,2,9)\ A(175,7,2,5,2)\N(4,4,3)\C(9,0)\ C(9,0)\N(8,0,1)\ C(9,10)\S(1,1,0.8)\N(2,5,2)\C(9,2)\ R(164,2,6,3,F)\C(9,4)\S(1,0.9,1)\ R(357,4,3,8,F)

G12-02

N(4,0,3,)\A(057,4,3,6,3)\A(082,0,0,2,1)\ R(324,9,2,8,T)\N(5,2,9,)\C(9,5)\ M(9,7)\M(9,7)\R(039,0,7,2,F)\ N(3,3,1,)\N(1,7,3)\ C(9,7)\M(9,3)\C(9,7)\R(027,6,2,2,F)\ A(192,3,7,1,4)\S(1.7,1.7,1)\ M(9,7)\R(03,5,3,1,F)\C(9,2)\C(9,2)\ R(175,0,1,9,F)

G12-07

S(0.9,1,0.9)\N(9,3,2,)\C(9,7)\ M(9,7)\A(223,1,2,5,2)\S(1.9,1.9,1.9)\ A(093,1,4,6,5)\C(9,6)\ S(2.1,1,1)\R(241,5,1,6,T)\ M(9,4)\C(9,4)\ S(1,1,1.4)\R(117,3,4,0,F)\ S(1.5,1.5,1.5)\A(104,0,1,1,7)\ A(096,3,4,6,4)\C(9,2)

Population 12

G12-03

G12-04

G12-08

G12-09

C(9,7)\C(9,7)\R(198,9,1,0,F)\C(9,4)\ A(263,4,8,3,9)\M(9,5)\ A(341,2,8,4,9)\C(9,2)\C(9,2)\M(9,2)\C(9,5)\ R(122,0,6,0,T)\ C(9,7)\A(340,3,6,5,4)\C(9,4)\C(9,4)\C(9,5)\ S(0.7,0.7,0.7)\N(1,1,2,)\M(9,4)\C(9,4)\ R(283,7,1,2,T)

C(9,7)\S(2.3,2.3,2.3)\C(9,7)\C(9,)\C(9,7)\ R(312,0,8,1,T)\ C(9,3)\A(272,8,0,6,4)\R(059,0,4,6,F)\ N(2,6,5)\N(1,7,9)\S(2,2,2)\ A(211,1,6,2,4)\M(9,4)\C(9,4)\C(9,4)\ C(9,3)\C(9,10)\M(9,10)

C(9,7)\N(1,1,6)\N(2,6,8)\ C(9,7)\C(9,7)\C(9,)\R(321,5,7,1,T)\ A(151,8,6,7,5)\S(0.5,0.5,1)\ C(9,7)\N(5,1,1)\A(025,9,9,4,8)\ N(1,5,1)\C(9,3)\ N(3,7,6)\N(6,2,5)\S(0.8,0.8,0.8)\C(9,3)\

M(9,7)\C(9,7)\N(2,1,5)\ S(2.4,2.4,1)\M(9,3)\ N(3,4,6,)\R(322,3,1,8,T)\S(1,1,1)\ N(9,5,7,)\C(9,1)\ C(9,7)\M(9,10)\ S(2.5,2.5,2.5)\S(1,1.8,1.8)\ A(150,7,7,1,9)\M(9,6)\C(9,6)\ A(091,2,4,9,8)\N(1,6,0,)\A(070,6,1,8,3)

G12-05

C(9,7)\C(9,7)\S(1.2,1.2,1.2)\C(9,3)\ R(312,6,1,0,F)\C(9,7)\R(297,4,4,4,T)\ C(9,7)\N(3,4,4)\ S(1.2,1.2,1.2)\S(1.2,1.2,1.2)\ A(199,8,4,4,1)\R(257,1,4,7,F)\ R(337,9,6,7,F)\M(9,3)\N(1,8,1)\ R(129,1,6,1,T)\

G12-10

C(9,10)\S(0.6,1,0.6)\M(9,3)\C(9,3)\ N(0,1,1)\A(358,5,8,2,6)\ A(321,0,1,2,3)\A(353,9,9,9,4)\C(9,)\ R(088,0,1,8,T)\ S(1.5,1,1.5)\S(2.1,1,1)\ C(9,10)\A(280,4,4,0,8)\ A(076,9,4,5,4)\S(2,2,2)\ C(9,6)\A(119,1,6,3,2)\M(9,4)\C(9,4)\ R(138,0,3,6,F)\C(9,1)

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Sequence 04

Population 12

4093 6614 2694 1883 791 2405 2807 ULL ULL ULL

SINDIVIDUAL S/V # 5359 2626 2048 1461 628 1944 2329 NULL NULL NULL

0.38 8 0.40 9 0.76 4 0.78 5 0.79 1 0.80 2 0.83 6 NULL 3 NULL 7 NULL 10

S/V

N. DISTRIBUTION

14093 6614 2694 1883 791 2405 2807 NULL NULL NULL

5359 2626 2048 1461 628 1944 2329 NULL NULL NULL

0.38 0.40 0.76 0.78 0.79 0.80 0.83 NULL NULL NULL

6.51E-01 7.54E-01 1.85E+00 1.76E+00 1.72E+00 1.67E+00 1.50E+00 NULL NULL NULL

MEAN 0.68 S.DEVIATION 0.20

0.68 0.20

The individuals of Population 12 were ranked according to the Exposure Ratio (S/V). As can be seen from the graph, the distribution of Population 12 does not approximates a normal distribution. However, the standard deviation is close to 0.00; this means that the Exposure Ratios of the individuals are generally close to the mean value. In addition, some of the individuals (3 out of 10) have NULL values since they could not be evaluated and were killed.

N. DISTRIBUTION

2.50

6.51E-01 7.54E-01 1.85E+00 1.76E+00 2.00 1.72E+00 1.67E+00 1.50E+00 NULL 1.50 NULL NULL

1.00

Population ten is evaluated for the best Surface area / Volume Ratio. The fittest individuals are cross-bread in order to generate population 11.

0.50

0.00 0.00

G12-08

0.20

0.40

G12-09

0.60

0.80

1.00

G12-04

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Sequence 04

Rather then cross breading only the fittest individuals of this generation , the two fittest and one average individual are cross bread. Transactional, deletion, and duplication are being used.

G13-01

C(9,7)\C(9,1)\C(9,7)\R(312,0,8,1,T)\ C(9,7)\S(2.3,2.3,2.3)\C(9,7)\C(9,)\C(9,7)\ R(312,0,8,1,T)\ C(9,3)\A(272,8,0,6,4)N(2,6,5)\N(1,7,9)\ S(2,2,2)\C(9,3)\A(272,8,0,6,4)\ R(059,0,4,6,F)\N(2,6,5)\N(1,7,9)\S(2,2,2)\ A(211,1,6,2,4)\M(9,4)\C(9,4)\C(9,4)\ A(211,1,6,2,4)\M(9,4)\C(9,4)\C(9,4)\ C(9,3)\C(9,10)\C(9,10)\M(9,10)

G13-06

M(9,7)\C(9,7)\N(2,1,5)\N(2,6,8)\ N(3,4,6)\R(322,3,1,8,T)\ R(321,5,7,1,T)\ A(151,8,6,7,5)\S(0.5,0.5,1)\ C(9,7)\M(9,10)\N(1,5,1)\C(9,3)\ A(150,7,7,1,9)\M(9,6)\C(9,6)\ A(150,7,7,1,9)\S(0.8,0.8,0.8)\C(9,3)

G13-02

C(9,7)\C(9,)\C(9,7)\R(312,0,8,1,T)\M(9,7)\ C(9,7)\N(2,1,5,)\S(2.4,2.4,1)\M(9,3)\ C(9,3)\A(272,8,0,6,4)\N(3,4,6)\ R(322,3,1,8,T)\S(1,1,1)\N(9,5,7,)\C(9,1)\ C(9,7)\M(9,3)\C(9,7)\R(027,6,2,2,F)\ A(211,1,6,2,4)\M(9,4)\C(9,4)\C(9,4)\ S(2.5,2.5,2.5)\S(1,1.8,1.8)\ C(9,3)\C(9,10)\C(9,6)\A(091,2,4,9,8) N(1,6,0)\A(070,6,1,8,3)\

G13-07

Population 13

G13-03

C(9,7)\S(2.3,2.3,2.3)\C(9,7)\C(9,)\C(9,7)\ R(312,0,8,1,T)\N(2,1,5,)\S(2.4,2.4,1)\M(9,3)\ N(1,7,9)\S(2,2,2)\N(3,4,6)\R(322,3,1,8,T)\ A(211,1,6,2,4)\M(9,4)\C(9,7)\M(9,10)\ S(2.5,2.5,2.5)\S(1,1.8,1.8)\ C(9,3)\C(9,10)\M(9,10)\A(150,7,7,1,9)\ M(9,6)\C(9,6)\A(091,2,4,9,8)\ A(150,7,7,1,9)\M(9,6)

N(1,1,6)\S(2.3,2.3,2.3)\C(9,7)\C(9,7)\ C(9,)\C(9,7)\ C(9,7)\R(321,5,7,1,T)\S(0.5,0.5,1)\ A(272,8,0,6,4)\N(2,6,5)\ N(5,1,1)\N(1,5,1)\C(9,3)\ A(211,1,6,2,4)\C(9,4)\ S(0.8,0.8,0.8)\M(9,10)

G13-08

G13-04

G13-05

C(9,7)\S(2.3,2.3,2.3)\C(9,7)\C(9,5)\C(9,7)\ R(312,0,8,1,T)\ N(3,4,6,)\R(322,3,1,8,T)\S(1,1,1)\ N(9,5,7)\C(9,1)\ A(211,1,6,2,4)\M(9,4)\C(9,4)\C(9,4)\ A(150,7,7,1,9)\M(9,6)\C(9,6)\A(091,2,4,9,8)\ N(1,6,0,)\A(070,6,1,8,3)

N(2,6,8,)\N(2,1,5,)\S(2.4,2.4,1)\M(9,3)\ C(9,7)\C(9,7)\C(9,5)\N(3,4,6)\ R(322,3,1,8,T)\ C(9,7)\N(5,1,1)\A(025,9,9,4,8)\ C(9,7)\M(9,10)\ \S(0.8,0.8,0.8)\C(9,3)\S(0.8,0.8,0.8)\ C(9,3)\A(091,2,4,9,8)\ N(1,6,0)\A(070,6,1,8,3)

S(2.4,2.4,1)\M(9,3)\M(9,7)\ C(9,7)\N(2,1,5)\ S(1,1,1)\N(9,5,7,)\C(9,1)\N(3,4,6,)\ R(322,3,1,8,T)\ S(1,1.8,1.8)\C(9,7)\M(9,10)\ S(2.5,2.5,2.5)\C(9,7)\ A(091,2,4,9,8)\N(1,6,0)\A(070,6,1,8,3)\ A(150,7,7,1,9)\M(9,6)\C(9,6)

G13-09

C(9,7)\N(1,1,6)\N(2,6,8)\ C(9,7)\C(9,7)\C(9,5)\R(321,5,7,1,T)\ A(151,8,6,7,5)\S(0.5,0.5,1)\ C(9,7)\N(5,1,1)\A(025,9,9,4,8)\ N(1,5,1)\C(9,3)\ N(3,7,6,)\N(6,2,5)\S(0.8,0.8,0.8)\C(9,3)

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 04

Population 13

9680 0465 2424 2134 3394 7944 2581 1920 ULL

SINDIVIDUAL S/V # 8460 10003 4437 4500 5135 3644 2161 1700 NULL

0.29 3 0.33 1 0.36 7 0.37 4 0.38 5 0.46 2 0.84 9 0.89 6 NULL 8

MEAN 0.49 S.DEVIATION 0.24

S/V

N. DISTRIBUTION

29680 30465 12424 12134 13394 7944 2581 1920 NULL

8460 10003 4437 4500 5135 3644 2161 1700 NULL

0.29 0.33 0.36 0.37 0.38 0.46 0.84 0.89 NULL

1.18 1.34 1.45 1.48 1.51 1.67 0.57 0.40 NULL

0.49 0.24

The individuals of Population 13 were ranked according to the Exposure Ratio (S/V). As can be seen from the graph, the distribution of Population 13 approximates the normal distribution. As for the standard deviation of Population 13, the table clearly highlights that the value is approximately as low as the one related to Population 12; this means that overall the Exposure Ratio of the individuals are close to the mean value. In particular, only 2 out of 15 individuals (G13-06 and G13-08) are more than one standard deviation from the mean.

N. DISTRIBUTION

1.80 1.60 1.40 1.20 1.00

1.18 1.34 1.45 1.48 1.51 1.67 0.57 0.40 NULL

0.80 0.60 0.40 0.20 0.00 0.00

0.20

0.40

0.60

0.80

1.00

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi Dâ&#x20AC;&#x2122;Acunto Norman Hack Camila Rock Pablo Zamorano

Sequence 04 Conclusions

POPULATION 12

POPULATION 13

3 2 1

G13-01

G12-02

G13-02

SEXUAL REPRODUCTION

G13-03

SEXUAL REPRODUCTION

2 FITTEST

G12-01

ASEXUAL REPRODUCTION

G12-03 G12-04

G12-08 G12-09

G12-05 1

G12-06

G12-07

3 4

As a conclusion we think the application of genetic algorithms in architecture has the potential to create unexpected high per formative design solutions. A crucial point to a successful use of the GA lies in the definition of the fitness criteria, the environmental pressure and a sensitive definition of the points of mutation.

2 FITTEST AND 1 AVERAGE

G12-08 G12-09

1 AVERAGE

SCRIPT APPLIED TO THE PRIMITIVE

2-8 OPERATIONS RANDOMLY CHOSEN FOR EACH SEGMENT OF THE INDIVIDUAL BETWEEN 6 BASIC RHINO OPERATIONS

G12-04

CROSS BREEDING STRATEGY

PRIMITIVE

G13-04

SEXUAL REPRODUCTION

G13-05

ASEXUAL REPRODUCTION

G13-06

SEXUAL REPRODUCTION

G13-07

SEXUAL REPRODUCTION

G13-08

SEXUAL REPRODUCTION

G13-09

ASEXUAL REPRODUCTION

In our experiments the definition of the fitness criteria changed over the term of the 13 populations so that no increasing fitness over the term of all populations could be detected. Also the environmental pressure was too weak, which resulted in a rather “unspecialised” individuals. In order to use GAs for architectural design it seems to be crucial that the fitness criteria against which the individuals are tested is quantifiable . For example spacial quality can hardly be measured in numbers while e.g. structural performance can be. Here we see an interesting aspect for further research. In order to work effectively the GA must incorporate feedback loops of generation and evaluation. Most software packages offer either one or the other option. An interface between an FEM software which evaluates the quality of a structure and programmable CAD software like Rhino would be desirable.

G12-10 ASEXUAL REPRODUCTION

Emergent Technologies & Design EMERGENCE SEMINAR Documentation - Jan 2011

Pierluigi D’Acunto Norman Hack Camila Rock Pablo Zamorano