1. 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

2. 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 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: We found in the loop populations: 1. Diversities in macro-scale morphologies and mutational biases 2. Genetic adaptation 3. Genetic diversification and continuing exploration

3. 3 Background: CA-based Alife Universal constructor (Von Neumann 1966; Codd 1968; Takahashi et al. 1990; Pesavento 1995) 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-replicating loops (Langton 1984; Byl 1989; Reggia et al. 1993) Self-inspecting loops/worms (Ibanez et al. 1995; Morita et al. 1995, 1996) 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) 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) 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. 4 Supposedly Limited Evolutionary Dynamics in CA McMullin (2000): 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): Suzuki et al. (2003): “Though there are many other variations of CA models for self-replication, their evolvability does not differ very much.”

5. 5 Question Did we truly understand what was going on in this seemingly simple dynamics of our CA-based evolutionary systems? 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. 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. 6 Subject: Evoloop An evolvable SR loop by Sayama (1999) constructed on nine-state five- neighbor fully deterministic CA 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 Robust state- transition rules give rise to evolutionary behavior Mutation/selection mechanisms are totally emergent Mutation/selection mechanisms are totally emergent

7. 7 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 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 Each genotype-phenotype pair is indexed in the Species Databasegenotype GGGGCGCGTT GCCCCG phenotype 8 8

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

9. 9 Huge Genetic State-Space Permutation of genes ( G, T ) and core states ( C ) under constraints estimates the number of viable genotypes to be Permutation of genes ( G, T ) and core states ( C ) under constraints estimates the number of viable genotypes to be Size n # of species Size n # of species Size n # of species 415911,440149,657,700 5561043,7581537,442,160 621011167,96016145,422,675 779212646,64617565,722,720 83,003132,496,144182,203,961,430 2n-2 n-2

10. 10 Diversity in Growth Patterns (size-4)

11. 11 Diversity in Growth Patterns (size-6)

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

13. 13 Observation (2): Genetic Adaptation

14. 14 Two Measures of (Possible) Fitness Survival rate (sustainability in competition): 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): 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. 15 Variety and Correlation (size-4)

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

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

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

19. 19 Non-Mutable Subsequences Certain subsequences are found non-mutable: Certain subsequences are found non-mutable: G{C*}T{C*}TG 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 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 Such “GMO” loops show long-lasting evolutionary exploration processes GGGGCGC GCCTCCTG G

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

21. 21 Conclusions Huge diversity, non-trivial genetic adaptation and diversification unveiled in the evoloop system 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 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. 22 References & Acks Salzberg, C. (2003) Emergent Evolutionary Dynamics of Self- Reproducing Cellular Automata. M.Sc. Thesis. Universiteit van Amsterdam, the Netherlands. 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. 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/ 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/ Antony, A. & Salzberg, C. The Artis Project Homepage. http://artis.phenome.org/ 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.