Abstract
In this paper we measure genomic properties in EvoDevo systems, to predict emergent phenotypic characteristic of artificial organisms. We describe and compare three parameters calculated out of the composition of the genome, to forecast the emergent behavior and structural properties of the developed organisms. The parameters are each calculated by including different genomic information. The genotypic information explored are: purely regulatory output, regulatory input and relative output considered independently and an overall parameter calculated out of genetic dependency properties. The goal of this work is to gain more knowledge on the relation between genotypes and the behavior of emergent phenotypes. Such knowledge will give information on genetic composition in relation to artificial developmental organisms, providing guidelines for construction of EvoDevo systems. A minimalistic developmental system based on Cellular Automata is chosen in the experimental work.
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References
Binder, P.M.: A Phase Diagram for Elementary Cellular Automata. Complex Systems 7, 241–247 (1993)
Binder, P.M.: Parametric Ordering of Complex Systems. Physical Review E 49(3), 2023–2025 (1994)
De Oliveira, G., De Oliveira, P., Omar, N.: Guidelines for Dynamics-based Parametrization of One-Dimensional Cellular Automata Rule Space. Complexity 6(2) (2001)
De Oliveira, G., De Oliveira, P., Omar, N.: Definition and Application of a Five-Parameter Characterization of One-Dimensional Cellular Automata Rule Space. Artificial Life 7, 277–301 (2001)
Li, W.: Phenomenology of Nonlocal Cellular Automata. Journal of Statistical Physics 68(5-6), 829–882 (1992)
Tufte, G., Nichele, S.: On the correlations between developmental diversity and genomic composition. In: GECCO 2011, pp. 1507–1514. ACM (2011)
Nichele, S., Tufte, G.: Trajectories and Attractors as Specification for the Evolution of Behavior in Cellular Automata. In: IEEE CEC 2010, pp. 4441–4448 (2010)
Beer, R.D.: A dynamical systems perspective on agent-environment interaction. Artificial Intelligence 72(1-2), 173–215 (1995)
Bentley, P.J., Kumar, S.: Three ways to grow designs: A comparison of embryogenies for an evolutionary design problem. In: GECCO 1999, pp. 35–43 (1999)
Cussat-Blanc, S., Luga, H., Duthen, Y.: From single cell to simple creature morphology and metabolism. In: Bullock, S., Noble, J., Watson, R., Bedau, M.A. (eds.) Artificial Life XI, pp. 134–141. MIT Press, Cambridge (2008)
Eggenberger, P.: Evolving morphologies of simulated 3d organisms based on differential gene expression. In: 4th Artificial Life Conference, pp. 205–213. MIT Press (1997)
Fleischer, K., Barr, A.H.: A simulation testbed for the study of multicellular development: The multiple mechanisms of morphogenesis. In: 3rd Artificial Life Conference, pp. 389–416. Addison-Wesley (1993)
Forrest, S.: Emergent Computation. MIT Press (1991)
Gordon, T.G.W.: Exploring models of development for evolutionary circuit design. In: IEEE CEC 2003, pp. 2050–2057. IEEE (2003)
Hall, B.K., Pearson, R.D., Müller, G.B.: Environment, development, and Evolution Toward a Synthesis. The Vienna Series in Theoretical Biology. MIT-Press (2004)
Kitano, H.: Building Complex Systems Using Developmental Process: An Engineering Approach. In: Sipper, M., Mange, D., Pérez-Uribe, A. (eds.) ICES 1998. LNCS, vol. 1478, pp. 218–229. Springer, Heidelberg (1998)
Kowaliw, T.: Measures of complexity for artificial embryogeny. In: GECCO 2008. ACM (2008)
Kowaliw, T., Grogono, P., Kharma, N.: Environment as a spatial constraint on the growth of structural form. In: GECCO 2007, New York, USA, pp. 1037–1044 (2007)
Kumar, S., Bentley, P.J.: Biologically Inspired Evolutionary Development. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds.) ICES 2003. LNCS, vol. 2606, pp. 57–68. Springer, Heidelberg (2003)
Langton, C.G.: Self-reproduction in cellular automata. Physica D 10, 135–144 (1984)
Langton, C.G.: Computation at the edge of chaos: phase transitions and emergent computation. In: Forrest, S. (ed.) Emergent Computation, pp. 12–37. MIT Press (1991)
Lehre, P.K., Haddow, P.C.: Developmental mappings and phenotypic complexity. In: Congress on Evolutionary Computation (CEC 2003), pp. 62–68. IEEE (2003)
Miller, J.F.: Evolving a Self-Repairing, Self-Regulating, French Flag Organism. In: Deb, K., Tari, Z. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 129–139. Springer, Heidelberg (2004)
Miller, J.F., Banzhaf, W.: Evolving the program for a cell: from french flag to boolean circuits. In: Kumar, S., Bentley, P.J. (eds.) On Growth, Form and Computers, pp. 278–301. Elsevier Limited, Oxford (2003)
Mitchell, M., Hraber, P.T., Crutchfield, J.P.: Revisiting the egde of chaos: Evolving cellular automata to perform computations. Complex Systems 7, 89–130 (1993)
Packard, N.H.: Adaptation Toward the Edge of Chaos. In: Dynamic Patterns in Complex Systems, pp. 293–301. World Scientific (1988)
Tufte, G.: Evolution, development and environment toward adaptation through phenotypic plasticity and exploitation of external information. In: Bullock, S., Noble, J., Watson, R., Bedau, M.A. (eds.) Artificial Life XI, pp. 624–631. MIT Press, Cambridge (2008)
West-Eberhard, M.J.: Developmental Plasticity and Evolution. Oxford Univ. Press (2003)
Wolfram, S.: Universality and complexity in CA. Physica D 10(1-2), 1–35 (1984)
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Nichele, S., Tufte, G. (2012). Genome Parameters as Information to Forecast Emergent Developmental Behaviors. In: Durand-Lose, J., Jonoska, N. (eds) Unconventional Computation and Natural Computation. UCNC 2012. Lecture Notes in Computer Science, vol 7445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32894-7_18
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DOI: https://doi.org/10.1007/978-3-642-32894-7_18
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