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Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees

Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees

Taro Yabuki, Hitoshi Iba
Copyright: © 2005 |Pages: 21
ISBN13: 9781591403128|ISBN10: 159140312X|EISBN13: 9781591403142
DOI: 10.4018/978-1-59140-312-8.ch004
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MLA

Yabuki, Taro, and Hitoshi Iba. "Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees." Recent Developments in Biologically Inspired Computing, edited by Leandro Nunes de Castro and Fernando J. Von Zuben, IGI Global, 2005, pp. 61-81. https://doi.org/10.4018/978-1-59140-312-8.ch004

APA

Yabuki, T. & Iba, H. (2005). Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees. In L. Nunes de Castro & F. Von Zuben (Eds.), Recent Developments in Biologically Inspired Computing (pp. 61-81). IGI Global. https://doi.org/10.4018/978-1-59140-312-8.ch004

Chicago

Yabuki, Taro, and Hitoshi Iba. "Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees." In Recent Developments in Biologically Inspired Computing, edited by Leandro Nunes de Castro and Fernando J. Von Zuben, 61-81. Hershey, PA: IGI Global, 2005. https://doi.org/10.4018/978-1-59140-312-8.ch004

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Abstract

In this chapter, a new representation scheme for Genetic Programming (GP) is proposed. We need a Turing-complete representation for a general method of generating programs automatically; that is, the representation must be able to express any algorithms. Our representation is a recurrent network consisting of trees (RTN), which is proved to be Turing-complete. In addition, it is applied to the tasks of generating language classifiers and a bit reverser. As a result, RTN is shown to be usable in evolutionary computing.

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