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Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction
1Univ. of Tennessee Space Inst., Tullahoma, TN.
Abstract:
In a radial basis function (RBF) network, the RBF centers and widths can be evolved by a cooperative-competitive genetic algorithm. The set of genetic strings in one generation of the algorithm represents one REP network, not a population of competing networks. This leads to moderate computation times for the algorithm as a whole. Selection operates on individual RBFs rather than on whole networks. Selection therefore requires a genetic fitness function that promotes competition among RBFs which are doing nearly the same job while at the same time promoting cooperation among RBFs which cover different parts of the domain of the function to be approximated. Niche creation resulting from a fitness function of the form |w(i)|(beta)/E(|w(i')|(beta)), 1
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