Abstract
In this paper, we show applications of fuzzy rule-based systems to soccer agents. The task for them is to pass the ball to each other without being captured it by an opponent agent. That is, agents should reach quickly to the ball when receiving it, and consider pass timing in terms of an opponent's situation when passing.We define the former situation as the ball intercept problem, and the latter as the ball pass/dribble problem.We have proposed the learning method for the ball intercept problem. In this paper, we first introduce this method for acquiring the behavior.problem, and improve the behavior of soccer agents using another fuzzy rule-based system that turn angles. Then the ball/pass problem is described. Through computational experiments, we conclude that the learning agents can successfully acquire the behavioraccording to situations.
