基于适应度景观学习进化计算的虚拟适应度评价框架

Taku Hasegawa, Kaname Matsumura, Kaiki Tsuchie, N. Mori, Keinosuke Matsumoto
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引用次数: 3

摘要

在进化计算中引入机器学习技术是扩展进化计算设计的重要问题之一。本文提出了一种将遗传算法和支持向量机相结合的方法来实现不需要实际适应度评估的假想进化。
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Novel virtual fitness evaluation framework for fitness landscape learning evolutionary computation
Introducing the machine learning technique into evolutionary computation (EC) is one of the most important issues to expand EC design. In this paper, we proposed a novel method that combines the genetic algorithm and support vector machine to achieve the imaginary evolution without real fitness evaluations.
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