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Maximizing adaptive power in neuroevolution

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  • Paolo Pagliuca
  • Nicola Milano
  • Stefano Nolfi

Abstract

In this paper we compare systematically the most promising neuroevolutionary methods and two new original methods on the double-pole balancing problem with respect to: the ability to discover solutions that are robust to variations of the environment, the speed with which such solutions are found, and the ability to scale-up to more complex versions of the problem. The results indicate that the two original methods introduced in this paper and the Exponential Natural Evolutionary Strategy method largely outperform the other methods with respect to all considered criteria. The results collected in different experimental conditions also reveal the importance of regulating the selective pressure and the importance of exposing evolving agents to variable environmental conditions. The data collected and the results of the comparisons are used to identify the most effective methods and the most promising research directions.

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  • Paolo Pagliuca & Nicola Milano & Stefano Nolfi, 2018. "Maximizing adaptive power in neuroevolution," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-27, July.
    • Handle: RePEc:plo:pone00:0198788
    DOI: 10.1371/journal.pone.0198788
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    Cited by:

    1. Paolo Pagliuca & Stefano Nolfi, 2019. "Robust optimization through neuroevolution," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-27, March.

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