Successive adaptation of fuzzy rule-based systems in a multi-agent model

This paper examines the adaptability of fuzzy systems to gradual and sudden changes in the environment of a market selection game. Agents use fuzzy systems for iterative game playing. Training data are successively generated from each round of our game as a result of the market selection by fuzzy systems.

[1]  Hisao Ishibuchi,et al.  Fuzzy Q-learning for a multi-player non-cooperative repeated game , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[2]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[3]  Hisao Ishibuchi,et al.  Evolution of unplanned coordination in a market selection game , 2001, IEEE Trans. Evol. Comput..

[4]  Hisao Ishibuchi,et al.  Successive adaptation of neural networks in a multi-agent model , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[5]  John Yen,et al.  Improving the interpretability of TSK fuzzy models by combining global learning and local learning , 1998, IEEE Trans. Fuzzy Syst..

[6]  Hisao Ishibuchi,et al.  Learning fuzzy rules from iterative execution of games , 2003, Fuzzy Sets Syst..