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Accelerating Real-Valued Genetic Algorithms Using Mutation-with-Momentum.

Title: Accelerating Real-Valued Genetic Algorithms Using Mutation-with-Momentum.
Authors: Zhang, Shichao; Jarvis, Ray; Temby, Luke1; Vamplew, Peter1; Berry, Adam1
Source: AI 2005: Advances in Artificial Intelligence. 2005, p1108-1111. 4p.
Abstract: Directed mutation has been proposed for improving the convergence speed of GAs on problems involving real-valued alleles. This paper proposes a directed mutation approach based on the momentum term used in gradient descent training of neural networks. Mutation-with-momentum is compared against gaussian mutation and is shown to regularly result in improvements in performance during early generations. A hybrid of momentum and gaussian mutation is shown to outperform either individual approach to mutation. [ABSTRACT FROM AUTHOR]
Database: Supplemental Index