Artificial evolutionary development [Elektronische Ressource] / Till Steiner. Technische Fakultät
120 pages
English

Artificial evolutionary development [Elektronische Ressource] / Till Steiner. Technische Fakultät

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120 pages
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Arti cial EvolutionaryDevelopmentTILL STEINERDissertationA thesis presented to theTechnische Fakultat of the Universitat Bielefeldin partial ful llment of the requirementsfor the degree ofDoctor rerum naturalisOctober 2010Printed on non-aging paper (DIN EN ISO 9706).iiAcknowledgementsWorking at the Honda Research Institute was an exciting opportunity for me. Notmany PhD-students have the chance to start their scienti c career as an employee of abig international enterprise. In this privileged and unusual setting, I began to explorethe somewhat exotic topic of computational evolutionary development back in 2006.I was acquainted with the basics of this scienti c eld from my previous internshipat Honda, and felt at home in the institute. Provided with exceptional supervisionand funding, it was the ideal starting point for my PhD. Who else can say that theyare sent to Singapore for a short research project, just because they would enjoy suchan experience and agree to pursue a PhD afterwards? Not to mention being allowedseveral conference visits per year throughout the course of my PhD... Additionally,I had the opportunity to take a peek into the organization of an industrial researchinstitute. I am starting to see the great value of having had this experience now.

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Publié le 01 janvier 2011
Nombre de lectures 21
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Arti cial Evolutionary
Development
TILL STEINER
Dissertation
A thesis presented to the
Technische Fakultat of the Universitat Bielefeld
in partial ful llment of the requirements
for the degree of
Doctor rerum naturalis
October 2010Printed on non-aging paper (DIN EN ISO 9706).
iiAcknowledgements
Working at the Honda Research Institute was an exciting opportunity for me. Not
many PhD-students have the chance to start their scienti c career as an employee of a
big international enterprise. In this privileged and unusual setting, I began to explore
the somewhat exotic topic of computational evolutionary development back in 2006.
I was acquainted with the basics of this scienti c eld from my previous internship
at Honda, and felt at home in the institute. Provided with exceptional supervision
and funding, it was the ideal starting point for my PhD. Who else can say that they
are sent to Singapore for a short research project, just because they would enjoy such
an experience and agree to pursue a PhD afterwards? Not to mention being allowed
several conference visits per year throughout the course of my PhD... Additionally,
I had the opportunity to take a peek into the organization of an industrial research
institute. I am starting to see the great value of having had this experience now. A very
close and amicable contact with my supervisor not only shaped my scienti c approach,
but also my general image of what a good working environment should be, as well as
my future professional plans.
That said, it seemed that the general concept of ’no free lunch’ (ironically, fundamental
to my scienti c eld), did not apply to me at that time. However, a severe disadvantage
showed up toward the end of my PhD in 2009: the global crisis which badly a ected
the nancial situation of the automobile industry coincided with my negotiations for
an extension of my contract. In addition, this had a huge e ect on the scienti c and
human resource strategy of the institute, and on its general working atmosphere. To
witness and to be part of a complete re-orientation of a small division within a global
enterprise is, in my opinion, one of the most important economic lessons to learn.
Luckily I was a ected by such an event at a formative stage of my career.
The nal phase of my PhD was governed by re-orientation. Despite the serious situ-
ation, the institute was able to o er me an extension of my contract. Nevertheless,
I decided to leave Honda to search for a new experience in a smaller, medium-sized
business. In retrospect, I am very grateful to the management board of the Honda
Research Institute for the o er. They certainly had to exert their in uence far beyond
what I was aware of at the time.
Many people have supported me doing scienti c work. The relation between their
e ort and impact is naturally non-linear. In one case, however, it is very clear. Thank
you, Bernhard, for all the time you spent with me in innumerable meetings and your
sympathy for the sometimes unusual problems of a PhD student. I will certainly follow
your ideals on my future professional and personal path.
somehow, every advantage has to be paid for by a disadvantage in another area
iiiThank you Yaochu, for teaching me the crafts of science: studies, statistical analysis,
condensation of the information and publication of the results would all have been
much harder without your advice.
Thank you, former colleagues at the HRI, especially Markus, Stefan, Lars, Martina,
Giles, Mathias, Nils, Sven, Sven, David, and of course my ’room-mate’ Lisa, for making
every day a fun day at the institute! (Also, for scienti c discussions, of course...)
I want to thank the University of Bielefeld for accepting this document as an external
PhD thesis. Especially, I am grateful to the university part of the scienti c committee:
Prof.-Dr. Helge Ritter, Prof.-Dr. Tim Nattkemper, and Dr. Thomas Hermann.
I thank my family for all their support during the PhD time, and throughout my life.
Kristin, thank you for all the love and having been there whenever I needed you.
ivContents
Acknowledgements iii
1. Introduction 1
2. The Paradigm: Embryogenesis 5
2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2. Building a Multicellular Organism . . . . . . . . . . . . . . . . . . . . . 6
2.2.1. An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2.2. Genes and Di erential Gene Expression During Embryogenesis . 6
2.2.3. Cellular Communication . . . . . . . . . . . . . . . . . . . . . . 9
2.2.4. The Four Stages of Embryogenesis . . . . . . . . . . . . . . . . 10
2.3. The Evolutionary Perspective on Embryogenesis . . . . . . . . . . . . . 12
2.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3. Simulation of Development 15
3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2. Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2.1. Dynamics of Development { Control Mechanisms . . . . . . . . 17
3.2.2. Cellular Simulation { Phenotypic Mechanisms . . . . . . . . . . 22
3.2.3. Discussion of Related Work . . . . . . . . . . . . . . . . . . . . 24
3.3. The Simulation Environment . . . . . . . . . . . . . . . . . . . . . . . . 25
3.3.1. Control Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . 25
3.3.2. Phenotypic Mechanisms . . . . . . . . . . . . . . . . . . . . . . 33
3.3.3. Evolution Strategy . . . . . . . . . . . . . . . . . . . . . . . . . 36
4. Graph-based Development 37
4.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2. Evolving Dynamical Motifs . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2.2. Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2.3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.2.4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.3. Developmental System Design . . . . . . . . . . . . . . . . . . . . . . . 45
4.3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.3.2. Experiment S: The Simpli ed Setup . . . . . . . . . . . . . . . . 45
4.3.3. Experiment C: The Complete Setup . . . . . . . . . . . . . . . . 47
4.3.4. Fitness Function . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.3.5. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
v4.3.6. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5. Vector Field Embryogeny 55
5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.2. Evolving Di erentiation . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.2.2. Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.2.3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.2.4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
5.3. Higher Level Principles of Development in Vector Field Embryogeny . . 62
5.3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
5.3.2. Hierarchy in Vector Field Embryogeny . . . . . . . . . . . . . . 62
5.3.3. Heterochrony in Vector Field Embryogeny . . . . . . . . . . . . 64
5.3.4. Allometry in Vector Field Embryogeny . . . . . . . . . . . . . . 66
5.3.5. Evolving Di erentiation Using Two Stage Spatial Hierarchy . . 67
5.3.6. Ev di eren with and without allometry . . . . . . . 68
5.3.7. Evolving Di erentiation Using Hierarchy and Allometry . . . . . 70
5.3.8. Ev Heterochrony . . . . . . . . . . . 70
5.3.9. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6. Evolvability of Graph- and Vector Field Embryogeny-representations 81
6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.2. A Prerequisite: Strong Causality and the Genotype to Phenotype Map 81
6.3. A Phenotype for Dynamical Systems . . . . . . . . . . . . . . . . . . . 82
6.3.1. Discrete Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.3.2. Field Di erence . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
6.4. Causality in Graph Based Modeling . . . . . . . . . . . . . . . . . . . . 83
6.5.y in Vector Field Embryogeny Based Modeling . . . . . . . . . 86
6.6. Comparison of Graph Based and Vector Field Embryogeny Based Modeling 86
6.7. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
7. Conclusion 91
A. GP Plots 95
B. Sequence Diagrams of the Arti cial Development-Simulation Environment
and the Vector Field Embryogeny Simulation 99
C. Bi-Linear Energy Calculation 103
Bibliography 107
vi1. Introduction
For the real amazement, if you wish to be amazed, is this process. You start
out as a single cell derived from the coupling of a sperm and an egg; this
divides in two, then four, then eight and so on, and at a certain stage there
emerges a single cell which has as all its progeny the human brain. The
mere existence of such a cell should be one of the great astonishments of the
earth. People ought to be walking around all day, all through their working
hours calling

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