Classifier systems that compute action mappings Pier Luca
نویسندگان
چکیده
The learning complexity of niche based learning classifier systems depends both on the complexity of the problem state space and on the number of available actions. In this paper, we introduce a version of XCS with computed actions, briefly XCSCA, that can be applied to problems involving a large number of actions. We report experimental results showing that XCSCA can evolve accurate and compact representations of binary functions which would be challenging for typical learning classifier system models.
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