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Complex Genetic Evolution of Self-Replicating Loops

Complex Genetic Evolution of Self-Replicating Loops. Chris Salzberg 1,2 Antony Antony 3 Hiroki Sayama 1 1 University of Electro-Communications, Japan 2 University of Tokyo, Japan 3 University of Amsterdam, the Netherlands sayama@cx.hc.uec.ac.jp. Summary.

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Complex Genetic Evolution of Self-Replicating Loops

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  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@cx.hc.uec.ac.jp

  2. 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

  3. 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)

  4. 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.”

  5. Question • Did we truly understand what was going on in this seemingly simple dynamics of our CA-based evolutionary systems? • We didn’t know we didn’t, until we have developed the formal framework and the sophisticated tools for detailed analysis and visualization for those systems.

  6. 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

  7. phenotype 8 8 genotype G C C C C G G G G G C G C G T T New Tools for Detailed Analysis • At every birth, the newborn loop’s 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

  8. Observation (1):Diversities in Macro-Scale Morphologies and Mutational Biases

  9. 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

  10. Diversity in Growth Patterns (size-4)

  11. Diversity in Growth Patterns (size-6)

  12. Diversity in Mutational Biases (size-6) (new result not included in paper)

  13. Observation (2):Genetic Adaptation

  14. 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

  15. Variety and Correlation (size-4)

  16. Evolution in vivo(starting from size-8)

  17. Evolution Optimizes “Fitness” Evolutionary transition actually observed in the previous slide

  18. Observation (3):Genetic Diversification and Continuing Exploration

  19. Non-Mutable Subsequences • Certain subsequences are found non-mutable: G{C*}T{C*}TG • A long non-mutable sub-sequence injected to ancestor causes a relatively largelower 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 GGGGCGC GCCTCCTG G

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

  21. 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

  22. 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.

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