We propose Mutation Systems as a model of the evolution of a string subject to the effects of mutations and a fitness function. One fundamental question about such a system is whether knowing the rules for mutations and fitness, we can predict whether it is possible for one string to evolve into another. To explore this issue we define a specific kind of mutation system with point mutations and a fitness function based on conserved strongly k-testable string patterns. We show that for k ≥ 2, such systems can simulate computation by both finite state machines and asynchronous cellular automata. The cellular automaton simulation shows that in this framework, universal computation is possible and the question of whether one string can evolve into another is undecidable. We also analyze the efficiency of the finite state machine simulation assuming random point mutations. © 2011 Springer-Verlag.
CITATION STYLE
Angluin, D., Aspnes, J., & Barbosa Vargas, R. (2011). Mutation systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6638 LNCS, pp. 92–104). Springer Verlag. https://doi.org/10.1007/978-3-642-21254-3_6
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