Some Methodological Issues about Designing Autonomous Agents Which Learn Their Behaviors: the Elf Experience

In this paper, we present our experience in developing behavior-based autonomous agents. We focus on methodological aspects of what we call Behavior Engineering, a new branch of engineering whose aim is to design and implement behavior-based agents. Once defined a behavior, we have to decide whether to implement it by programming the agent, or to make the agent learning its behavior. In this paper, we focus on this second aspect, and we report some results we obtained with a new machine learning algorithm (ELF Evolutionary Learning of Fuzzy Systems) learning behaviors described as sets of fuzzy rules. The characteristic features of ELF are that it can learn the only rules it needs to achieve its task, it is resistent to biased evaluation functions, and it can learn generalizazions.