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Incremental Evolution with Minimal Resources

Joseba Urzelai, Dario Floreano

发表年份
1999
引用次数
16
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摘要

This paper describes an evolutionary algorithm based on a statistical representation of populations of individuals. Experiments on robot navigation and on numerical fitness functions are presented in order to measure the performance of the algorithm compared to traditional genetic algorithms. Results show that the method is suitable for onboard online evolution because it requires low amount of memory resources. Furthermore, it allows for incremental evolution in dynamic environments in order to cope with complex tasks that require several evolutionary stages.

关键词

Evolutionary algorithmComputer scienceRepresentation (politics)Measure (data warehouse)Genetic algorithmArtificial intelligenceEvolutionary computationOrder (exchange)Machine learningData mining

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