経験的知識に基づく遺伝子操作を導入したGAによる効率的なモジュール構造型ロボットの迷路巡航学習

抄録

In this paper, we propose a genetic algorithm including genetic operator based on empirical knowledge. We demonstrate the advantages of the proposed method by applying it to a problem of navigation of robot. In the proposed method, when a robot can’t complete a task, the weight, which is corresponding to gene, of the activation network which decides the behavior of the robot is revised directly by using the empirical knowledge. Heuristic rules used in the genetic operator based on empirical knowledge are determined to constructs a robot which has better ability than before modified by designer. Computational experiments show that the proposed method raises fitness in earlier generation than the conventional GA.