Obtaining Repetitive Actions for Genetic Programming with Multiple Trees

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@Article{Ito:2016:PCS,

• author = "Takashi Ito and Kenichi Takahashi and Michimasa Inaba",
• title = "Obtaining Repetitive Actions for Genetic Programming with Multiple Trees",
• journal = "Procedia Computer Science",
• volume = "96",
• pages = "120--128",
• year = "2016",
• note = "Knowledge-Based and Intelligent Information and Engineering Systems: Proceedings of the 20th International Conference KES-2016",
• ISSN = "1877-0509",
• DOI = "doi:10.1016/j.procs.2016.08.111",
• URL = "http://www.sciencedirect.com/science/article/pii/S1877050916319123",
• abstract = "This paper proposes a method to improve genetic programming with multiple trees (GPCN). An individual in GPCN comprises multiple trees, and each tree has a number P that indicates the number of repetitive actions based on the tree. In previous work, a method for updating the number P has been proposed to obtain P suitable to the tree in evolution. However, in the method efficiency becomes worse as the range of P becomes wider. In order to solve the problem, in this study, two methods are proposed: inheriting the number P of a tree from an excellent individual and using mutation for preventing the number P from being into a local optimum. Additionally, a method to eliminate trees consisting of a single terminal node is proposed.",
• keywords = "genetic algorithms, genetic programming, autonomous agent, garbage collection problem, evolutionary learning, multiple trees.",

}

Genetic Programming entries for Takashi Ito Ken-ichi Takahashi Michimasa Inaba

Citations