Evolving Neural Networks for Classifier Prediction with XCSF
نویسندگان
چکیده
We extend XCS with computed prediction by replacing the usual linear prediction used in XCSF with a feedforward multilayer neural network. In XCSF with neural prediction, XCSFNN, classifier exploits a neural network to approximate the payoff surface associated to the target problem while the genetic algorithm adapts both classifier conditions, classifier actions, and the network structure. We compare XCSF with neural prediction to XCSF with linear prediction. Our results show that XCSFNN, outperforms XCSF when the target payoff is highly non linear and that genetic algorithm can effectively evolve the neural networks structure improving the approximation accuracy.
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