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arXiv · 1605.01514

Fitness-based Adaptive Control of Parameters in Genetic Programming: Adaptive Value Setting of Mutation Rate and Flood Mechanisms

Michal Gregor·Juraj Spalek
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Abstract

This paper concerns applications of genetic algorithms and genetic programming to tasks for which it is difficult to find a representation that does not map to a highly complex and discontinuous fitness landscape. In such cases the standard algorithm is prone to getting trapped in local extremes. The paper proposes several adaptive mechanisms that are useful in preventing the search from getting trapped.

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Michal Gregor, Juraj Spalek. 2016-05-05. Fitness-based Adaptive Control of Parameters in Genetic Programming: Adaptive Value Setting of Mutation Rate and Flood Mechanisms. https://arxiv.org/abs/1605.01514

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