Obtaining Repetitive Actions for Genetic Programming with Multiple Trees
Created by W.Langdon from
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- @Article{Ito:2016:PCS,
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author = "Takashi Ito and Kenichi Takahashi and
Michimasa Inaba",
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title = "Obtaining Repetitive Actions for Genetic Programming
with Multiple Trees",
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journal = "Procedia Computer Science",
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volume = "96",
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pages = "120--128",
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year = "2016",
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note = "Knowledge-Based and Intelligent Information and
Engineering Systems: Proceedings of the 20th
International Conference KES-2016",
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ISSN = "1877-0509",
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DOI = "doi:10.1016/j.procs.2016.08.111",
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URL = "http://www.sciencedirect.com/science/article/pii/S1877050916319123",
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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.",
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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