Learning classifier systems: From foundations to by Pier Luca Lanzi

By Pier Luca Lanzi

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I ignored the fact that classifiers can produce new messages so that the LCS has to deal with a message list, I ignored that a classifier can contain more than one condition and I ignored the possibility that more than one classifier can become active during one execution cycle. If there is more than one active classifier, then the LCS has to deal with inconsistent information for the output interface. There are two levels of learning in an LCS: A first level of learning called credit assignment, consists of reinforcement learning on the classifiers.

Fogel, Max H. Garzon, David E. Goldberg, Hitoshi Iba, and Rick Riolo, editors. Genetic Programming 1998: Proceedings of the Third Annual Conference. Morgan Kaufmann: San Francisco, CA, 1998. 45. Pier Luca Lanzi. A Study of the Generalization Capabilities of XCS. In B¨ ack [3], pages 418–425. gz. 46. Pier Luca Lanzi. Adding Memory to XCS. In Proceedings of the IEEE Conference on Evolutionary Computation (ICEC98). IEEE Press, 1998. gz. H. Holland et al. 47. Pier Luca Lanzi. Reinforcement Learning by Learning Classifier Systems.

45. Pier Luca Lanzi. A Study of the Generalization Capabilities of XCS. In B¨ ack [3], pages 418–425. gz. 46. Pier Luca Lanzi. Adding Memory to XCS. In Proceedings of the IEEE Conference on Evolutionary Computation (ICEC98). IEEE Press, 1998. gz. H. Holland et al. 47. Pier Luca Lanzi. Reinforcement Learning by Learning Classifier Systems. PhD thesis, Politecnico di Milano, 1998. 48. Pier Luca Lanzi. An Analysis of Generalization in the XCS Classifier System. Evolutionary Computation, 7(2):125–149, 1999.

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