A Fuzzy Evolutionary System for Concept Formation and Adaptive Behaviour in Software Agents

Software agent technology is currently based on fixed ontologies and languages, handcrafted for a particular application. The advent of massively distributed systems however calls for not only a common language between all agents involved but also the ability to autonomously adapt and form concepts about novel experiences and events. The authors proposed a method by which agents can autonomously form new concepts grounded in their own experience. This is an improvement on previous approaches because it can tackle a much wider range of conceptual types and provides an efficient, accurate representation, which can be used in a rule based system or conceptual framework. Furthermore, the method allowed an agent to simultaneously learn new concepts and the rules to govern its behaviour whilst providing a more robust system which is also adaptive