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XCS with Computed Prediction for the Learning of Boolean Functions
2005 IEEE Congress on Evolutionary Computation
Computed prediction represents a major shift in learning classifier system research. XCS with computed prediction, based on linear approximators, has been applied so far to function approximation, to single step problems involving continuous payoff functions, and to multi step problems. In this paper we take this new approach in a different direction and apply it to the learning of Boolean functions -a domain characterized by highly discontinuous 0/1000 payoff functions. We also extend it to
doi:10.1109/cec.2005.1554736
dblp:conf/cec/LanziLWG05
fatcat:wyjzigl23naphblr6djua4dbr4