A genetic algorithm discovers particle-based computation in cellular automata
How does evolution produce sophisticated emergent computation in systems composed of simple components limited to local interactions? To model such a process, we used a genetic algorithm (GA) to evolve cellular automata to perform a computational task requiring globally-coordinated information processing. On most runs a class of relatively unsophisticated strategies was evolved, but on a subset of runs a number of quite sophisticated strategies was discovered. We analyze the emergent logic underlying these strategies in terms of information processing performed by “particles” in space-time, and we describe in detail the generational progression of the GA evolution of these strategies. Our analysis is a preliminary step in understanding the general mechanisms by which sophisticated emergent computational capabilities can be automatically produced in decentralized multiprocessor systems.
KeywordsGenetic Algorithm Cellular Automaton Initial Configuration Regular Domain Deterministic Finite Automaton
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