Faster Learning of Control Parameters Through Sharing Experiences

Abstract

This paper describes a learning algorithm for small autonomous mobile robots based on sets of fuzzy automata. The task of the robots is to learn how to avoid obstacles reactively. The approach presented here is one in which two robots learn simultaneously, with the experiences of each robot being passed onto the other. It is shown that this sharing of experiences results in a faster and more repeatable learning of the robots' behavioural parameters when compared to individual learning