Generalized Evolutionary Algorithm based on Tsallis Statistics

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Generalized evolutionary algorithm based on Tsallis canonical distribution is proposed. The algorithm uses Tsallis generalized canonical distribution to weigh the configurations for `selection' instead of Gibbs-Boltzmann distribution. Our simulation results show that for an appropriate choice of non-extensive index that is offered by Tsallis statistics, evolutionary algorithms based on this generalization outperform algorithms based on Gibbs-Boltzmann distribution.
Submitted to Physical Review E, 5 pages, 6 figures

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Artificial Intelligence

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https://dspace.dare.co.zw/handle/123456789/43450

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arXiv

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