Complex Genetic Evolution of Self-Replicating Loops

1
Complex Genetic Evolution of Self-Replicating
Loops

• Chris Salzberg1,2 Antony Antony3 Hiroki
  Sayama1
• 1 University of Electro-Communications, Japan
• 2 University of Tokyo, Japan
• 3 University of Amsterdam, the Netherlands
• sayama_at_cx.hc.uec.ac.jp

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Summary

• We re-examined the evolutionary dynamics of
  self-replicating loops on CA, by using new tools
  for complete genetic identification and genealogy
  tracing
• We found in the loop populations
• Diversities in macro-scale morphologies and
  mutational biases
• Genetic adaptation
• Genetic diversification and continuing exploration

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Background CA-based Alife

• Universal constructor (Von Neumann 1966 Codd
  1968 Takahashi et al. 1990 Pesavento 1995)
• Self-replicating loops (Langton 1984 Byl 1989
  Reggia et al. 1993)
• Self-inspecting loops/worms (Ibanez et al. 1995
  Morita et al. 1995, 1996)
• Self-replicating loops with additional
  capabilities of construction/computation
  (Tempesti 1995 Perrier et al. 1996 Chou et al.
  1998)
• Spontaneous emergence and evolution of
  self-replicators (Lohn et al. 1995 Chou et al.
  1997 Sayama 1998, 2000, 2003 Salzberg et al.
  2003, 2004 Suzuki et al. 2003, 2004)

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Supposedly Limited Evolutionary Dynamics in CA

• McMullin (2000)
• SR loop does not embody anything like a
  general constructive automaton and therefore has
  little or no evolutionary potential.
• Suzuki et al. (2003)
• Though there are many other variations of CA
  models for self-replication, their evolvability
  does not differ very much.

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Question

• Did we truly understand what was going on in this
  seemingly simple dynamics of our CA-based
  evolutionary systems?
• We didnt know we didnt, until we have developed
  the formal framework and the sophisticated tools
  for detailed analysis and visualization for those
  systems.

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Subject Evoloop

• An evolvable SR loop by Sayama (1999) constructed
  on nine-state five-neighbor fully deterministic
  CA
• Robust state-transition rules give rise to
  evolutionary behavior
• Mutation/selection mechanisms are totally emergent

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New Tools for Detailed Analysis

• At every birth, the newborn loops genotype
  phenotype and its genealogical information is
  detected and recorded in an event-driven fashion
• Each genotype-phenotype pair is indexed in the
  Species Database

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Observation (1)Diversities in Macro-Scale
Morphologies and Mutational Biases
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Huge Genetic State-Space

• Permutation of genes (G, T) and core states (C)
  under constraints estimates the number of viable
  genotypes to be

2n-2 n-2
Size n of species Size n of species Size n of species
4 15 9 11,440 14 9,657,700
5 56 10 43,758 15 37,442,160
6 210 11 167,960 16 145,422,675
7 792 12 646,646 17 565,722,720
8 3,003 13 2,496,144 18 2,203,961,430
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Diversity in Growth Patterns (size-4)
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Diversity in Growth Patterns (size-6)
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Diversity in Mutational Biases (size-6)
(new result not included in paper)
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Observation (2)Genetic Adaptation
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Two Measures of (Possible) Fitness

• Survival rate (sustainability in competition)
• Characterized by an average of relative
  population ratios of a species after a given
  period of time in competition with another
  species
• Colony density index (growth speed)
• Characterized by a quadratic coefficient of a
  parabola fitted to the population growth curve of
  each species in an infinite domain

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Variety and Correlation (size-4)
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Evolution in vivo(starting from size-8)
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Evolution Optimizes Fitness
Evolutionary transition actually observed in the
previous slide
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Observation (3)Genetic Diversification and
Continuing Exploration
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Non-Mutable Subsequences
GGGGCGC GCCTCCTG G

• Certain subsequences are found non-mutable
• GCTCTG
• A long non-mutable sub-sequence injected to
  ancestor causes a relatively large lower bound of
  viable sizes upon its descendants, a reduced
  size-based selection pressure, and a highly
  biased mutational tendency to larger species
• Such GMO loops show long-lasting evolutionary
  exploration processes

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control
with long non-mutable subsequences
with subsequences hostile environment
(new result not included in paper)
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Conclusions

• Huge diversity, non-trivial genetic adaptation
  and diversification unveiled in the evoloop
  system
• Hierarchical emergence demonstrated, where
  macro-scale evolutionary changes of populations
  arises from micro-scale interactions between
  elements much smaller than individual
  replicators, traversing multiple scales

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References Acks

• Salzberg, C. (2003) Emergent Evolutionary
  Dynamics of Self-Reproducing Cellular Automata.
  M.Sc. Thesis. Universiteit van Amsterdam, the
  Netherlands.
• Salzberg, C., Antony, A. Sayama, H. Visualizing
  evolutionary dynamics of self-replicators A
  graph-based approach. Artificial Life, in press.
• Sayama, H. The SDSR loop / Evoloop Homepage.
  http//complex.hc.uec.ac.jp/sayama/sdsr/
• Antony, A. Salzberg, C. The Artis Project
  Homepage. http//artis.phenome.org/
• This work is supported in part by the Hayao
  Nakayama Foundation for Science, Technology
  Culture, and the International Information
  Science Foundation, Japan.