Volume 11 Number 4 (Jul. 2016)
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JCP 2016 Vol.11(4): 329-340 ISSN: 1796-203X
doi: 10.17706/jcp.11.4.329-340

Extension of Genetic Programming with Multiple Trees for Agent Learning

Takashi Ito, Kenichi Takahashi, Michimasa Inaba
Graduate School of Information Sciences Hiroshima City University, Hiroshima, Japan.
Abstract—This paper proposes an extension of genetic programming (GP) with multiple trees. In order to improve the performance, GP with control node (GPCN) and its three kinds of modification have been proposed. In GPCN, an individual consists of several trees which have the number P of executions. In previous work, the two kinds of modification, the conditional probability and the cross-cultural island model are employed. This paper proposes two methods: the new island model that combines the conditional probability with two islands in the cross-cultural island model and a method exchanges multiple trees in an individual in a suitable order. Experiments are conducted to show the performance in the garbage collection problem and the Santa Fe Trail problem.

Index Terms—Autonomous agent, conditional probability, genetic programming, island model.

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Cite: Takashi Ito, Kenichi Takahashi, Michimasa Inaba, "Extension of Genetic Programming with Multiple Trees for Agent Learning," Journal of Computers vol. 11, no. 4, pp. 329-340, 2016.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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