Abstract
In this paper, we use a cost-sensitive fuzzy system in a game environment. A cost-sensitive fuzzy system is generated so that the number of serious mistakes in decision making is minimized.Training data are generated from preliminary experiments.In computational experiments of this paper, cost-sensitive fuzzy systems are applied to a car-racing domain where two car agents compete for flags.We examine the performance of car agents with cost-sensitive fuzzy systems, standard fuzzy systems, and no fuzzy systems.Experimental results show the effectiveness of the cost-sensitive fuzzy systems for the game environment.
