Substitution of the Fittest: A Novel Approach for Mitigating Disengagement in Coevolutionary Genetic Algorithms

• URL: http://arxiv.org/abs/2108.03156v1
• Date: Fri, 6 Aug 2021 15:10:36 GMT
• Title: Substitution of the Fittest: A Novel Approach for Mitigating Disengagement in Coevolutionary Genetic Algorithms
• Authors: Hugo Alcaraz-Herrera and John Cartlidge
• Abstract summary: substitution of the fittest (SF) designed to counteract the problem of disengagement in two-population competitive coevolutionary genetic algorithms. In a minimal domain, we perform a controlled evaluation of the ability to maintain engagement and the capacity to discover optimal solutions.
• Score: 3.8073142980733
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose substitution of the fittest (SF), a novel technique designed to counteract the problem of disengagement in two-population competitive coevolutionary genetic algorithms. The approach presented is domain-independent and requires no calibration. In a minimal domain, we perform a controlled evaluation of the ability to maintain engagement and the capacity to discover optimal solutions. Results demonstrate that the solution discovery performance of SF is comparable with other techniques in the literature, while SF also offers benefits including a greater ability to maintain engagement and a much simpler mechanism.

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