Learning to coordinate fuzzy behaviors for autonomous agents

We developed a system learning behaviors represented as sets of fuzzy rules for autonomous agents. In the past, we adopted our approach to learn successfully simple reactive behaviors, also in those cases when the evaluation function used in our reinforcement learning schema judges unevenly the different situations the autonomous agents operate on. In this paper we present a new version of our approach that can learn to coordinate many different behaviors organized in classes of mutually exclusive behaviors. The present version of our algorithm gives satisfactory results also on this new task.