Classifier Systems for Continuous Payoff Environments
作者： Stewart W. Wilson
DOI: 10.1007/978-3-540-24855-2_96
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摘要: Recognizing that many payoff functions are continuous and depend on the input state x, classifier system architecture XCS is extended so a classifier’s prediction linear function of x. On nonlinear problem, system, XCS-LP, exhibits high performance low error, as well dramatically smaller evolved populations compared with XCS. Linear predictions seen new direction in quest for powerful generalization systems.
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sci-hub.se 参考文章(12)
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