Abstract
It is difficult to define a set of rules for a cellular automaton (CA) such that creatures with life-like properties (stability and dynamic behaviour, reproducton and self-repair) can be grown from a large number of initial configurations. This work describes an evolutionary framework for the search of a CA with these properties. Instead of encoding them directly into the fitness function, we propose one, which maximises the variance of entropy across the CA grid. This fitness function promotes the existence of areas on the verge of chaos, where life is expected to thrive. The results are reported for the case of CA in which cells are in one of four possible states. We also describe a mechanism for fitness sharing that successfully speeds up the genetic search, both in terms of number of generations and CPU time.
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References
De Jong, K.: An Analysis of the Behaviour of a Class of Genetic Adaptive Systems. PhD thesis, University of Michigan (1975)
Mitchell, M., Hraber, P.T., Crutchfield, J.P.: Revisiting the edge of chaos: Evolving cellular automata to perform computations. Complex Systems 7, 89–130 (1993)
Goldberg, D.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Holland, J.: Adaption in natural and artificial systems. University of Michigan Press (1975)
Hollstien, R.: Artificial Genetic Adaption in Computer Control Systems. PhD thesis, University of Michigan (1971)
Mahfoud, S.: Niching Methods for Genetic Algorithms. PhD thesis, University of Illinois, Urbana-Champaign (1995)
Dawkins, R.: The Extended Phenotype. Oxford University Press, Oxford (1982)
Falconer, D.: Introduction to Quantitative Genetics, 2nd edn. Longman, London (1981)
Packard, N.H.: Adaptation towards the Edge of Chaos. In: Dynamic Patterns in Complex Systems. World Scientific, Singapore (1988)
Sapin, E., Bailleux, O., Chabrier, J.: Research of complex forms in the cellular automata by evolutionary algorithms. In: Proc. of the 6th Intl. Conf. on Artificial Evolution, Marseille (2003)
Wolfram, S.: Statistical mechanics of cellular automata. Reviews of Modern Physics 55 (1983)
Wolfram, S.: Universality and complexity in cellular automata. Physica D 10, 1–35 (1984)
Basanta, D.: Evolving automata to grow patterns. Symposium on Evolvability and Interaction (2003)
Wolfram, S., Packard, N.: Two-dimensional cellular automata. Statistical Physics 38, 901–946 (1985)
Muggleton, S., Raedt, L.D.: Inductive logic programming: Theory and methods. Journal of Logic Programming 19, 20, 629–679 (1994)
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© 2005 Springer-Verlag Berlin Heidelberg
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Kazakov, D., Sweet, M. (2005). Evolving the Game of Life. In: Kudenko, D., Kazakov, D., Alonso, E. (eds) Adaptive Agents and Multi-Agent Systems II. AAMAS AAMAS 2004 2003. Lecture Notes in Computer Science(), vol 3394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32274-0_9
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DOI: https://doi.org/10.1007/978-3-540-32274-0_9
Publisher Name: Springer, Berlin, Heidelberg
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