Fuzzy dynamical genetic programming in XCSF

—A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to Neural Networks, and more recently Dynamical Genetic Programming (DGP). This paper presents results from an investigation into using a fuzzy DGP representation within the XCSF Learning Classifier System. In particular, asynchronous Fuzzy Logic Networks are used to represent the traditional condition-action production system rules. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such fuzzy dynamical systems within XCSF to solve two well-known test problems. Fuzzy Dynamical Genetic Programming in XCSF 

• Type: Journal
• Year: 2011
• Where: GECCO
• Authors: Richard Preen, Larry Bull
• Keywords: GECCO 2011, Learning Classifier System, Learning Classifier Systems, Logic Networks, Optimization