遺伝的プログラミング技法を用いた多出力二分決定グラフの進化 : 食物連鎖におけるマルチエージェントの進化シミュレーション

概要

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Genetic algorithm (GA) is an effective method to solve combinatorial optimization problems. The efficiency depends on how genes expressed. Although gene expression using finite state automata has already been proposed, it is not always suitable for genetic operation. We propose an gene expression using n-BDD, which lets genetic operations work efficiently. We show a simulation of Quasi-Ecosystem including herbivores, carnivores and plants as an experimental model to confirm the efficiency of our method compared with systems using finite state automata and classifier systems. Our experiments tell superiority of the n-BDD expression at the adjustment speed of animals' action strategy. In the Quasi-Ecosystem, strategies of animals' behavior are evolved in the genetic expressions. We also observed food chain in the environment, in which quick evolution of animals' behavior is necessary, using n-BDD expression.
社団法人人工知能学会の論文
1999-05-01