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Journal of Information Science and Engineering, Vol. 30 No. 3, pp. 669-686 (May 2014)


A Network Representation of First-Order Logic That Uses Token Evolution for Inference


HIDEAKI SUZUKI*, MIKIO YOSHIDA+ AND HIDEFUMI SAWAI*
*National Institute of Information and Communications Technology
Kobe, 651-2492, Japan
E-mail: {hsuzuki; sawai}@nict.go.jp
+BBR Inc.
Osaka, 530-0002, Japan
E-mail: yos@bbr.jp

A method to represent first-order predicate logic (Horn clause logic) by a data-flow network is presented. Like a data-flow computer for a von Neumann program, the proposed network explicitly represents the logical structure of a declarative program by unlabeled edges and operation nodes. In the deduction, the network first propagates symbolic tokens to create an expanded AND/OR network by the backward deduction, and then executes unification by a newly developed method to solve simultaneous equations buried in the network. The paper argues the soundness and completeness of the network in a conventional way, then explains how a kind of ambiguous solution is obtained by the newly developed method. Numerical experiments are also conducted with some data- flow networks, and the methods convergence ability and scaling property to larger problems are investigated.

Keywords: horn logic, data-flow network, inference, unification, evolution

Full Text () Retrieve PDF document (201405_08.pdf)

Received February 28, 2013; accepted June 15, 2013.
Communicated by Hung-Yu Kao, Tzung-Pei Hong, Takahira Yamaguchi, Yau-Hwang Kuo, and Vincent Shin-Mu Tseng.