Behavior generation for a mobile robot based on the adaptive fitness function

Eiji Uchibe, Masakazu Yanase, Minoru Asada

Abstract: We have to prepare the evaluation (fitness) function to evaluate the performance of the robot when we apply the machine learning techniques to the robot application. In many cases, the fitness function is composed of several aspects. Simple implementation to cope with the multiple fitness functions is a weighted summation. This paper presents an adaptive fitness function for the evolutionary computation to obtain the purposive behaviors through changing the weights for the fitness function. As an example task, a basic behavior in a simplified soccer game (shooting a ball into the opponent goal) is selected to show the validity of the adaptive fitness function. Simulation results and real experiments are shown, and a discussion is given.