A neural network approach to interference mechanism for logic programming language.

Autor:	Takeda, Yuji, Kawahara, Hideya, Kikuchi, Yukihiro, Murakoshi, Hideki, Funakubo, Noboru
Předmět:	NEURAL computers ARTIFICIAL neural networks ARTIFICIAL intelligence PROLOG (Computer program language) LOGIC programming languages PROGRAMMING languages COMBINATORIAL optimization MATHEMATICAL optimization
Zdroj:	Systems & Computers in Japan; 11/30/2004, Vol. 35 Issue 13, p63-70, 8p
Abstrakt:	It is known that the Hopfield-type neural network can solve the combinatorial optimization problem with a high speed. In order to realize that advantage, however, the energy function must be constructed for each problem, and there is no general framework to be applied to various problems. This paper notes that the logic programming language Prolog can be represented as the logical operation of facts and the rules, and proposes an algorithm, which converts the logical operation network to the Hopfield-type neural network. Using this conversion algorithm, the power of the Hopfield-type network as an optimization machine can be utilized in the logic inference described by Prolog. Then, it is expected that the range of its application will be enlarged greatly. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(13): 63–70, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10102 [ABSTRACT FROM AUTHOR]
Databáze:	Supplemental Index
Externí odkaz:	Zobrazit plný text záznamu Plný text