Abstract
The automatic creation of finite automata has long been a goal of the evolutionary computation community. The previous works in the evolution of finite state automata were limited to the evolution of strictly non-modular FSA. Here, a modular architecture to evolve FSA is proposed and a genetic programming procedure for evolving such structures is presented. Results on the Tomita Language benchmark indicate that the proposed procedure is indeed capable of successfully evolving modular FSA and that such modularity can result in a significantly increased rate of optimization.
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