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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Evolution of Program Teams
Erschienen in: Linear Genetic Programming
Verlag: Springer US
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This chapter applies linear GP to the evolution of cooperative teams to several prediction problems. Different linear methods for combining outputs of the team programs are compared. These include hybrid approaches where [1] a neural network is used to optimize the weights of programs in a team for a common decision and [2] a real-numbered vector (the representation of evolution strategies) of weights is evolved in tandem with each team. The cooperative team approach results in an improved training and generalization performance compared to the standard GP method.