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A neural network approach to inference mechanism for logic programming language

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4 Author(s)
Kawahara, H. ; Tokyo Metropolitan Inst. of Technol., Japan ; Murakoshi, H. ; Funakubo, N. ; Ishijima, S.

Presents an inference mechanism for logic programming languages using neural networks that is flexible and suited for fine-grain parallel computing. The authors approach is radically different from the conventional methods based on refutation processes. Programs written in the logic programming language are transformed into a Hopfield-type neural network and relaxation techniques are applied to this network to inference solutions. The authors propose an algorithm to transform logic programs into Hopfield-type neural networks and implement a prototype of the inference system based on this mechanism. The authors tested the system with some preliminary problems. Preliminary results confirm that the algorithm is correct.

Published in:

Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on  (Volume:1 )

Date of Conference:

25-29 Oct. 1993