Sudoku solver by q’tron neural networks

Authors:
Tai-Wen Yue;Zou-Chung Lee
Affiliations:
Dept. of Computer Science and Engineering, Tatung University, Taipei, Taiwan, R.O.C;Dept. of Computer Science and Engineering, Tatung University, Taipei, Taiwan, R.O.C
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

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Abstract

This paper presents a Sudoku solver based on the energydriven neural-network (NN) model, called the Q’tron NN model. The rules to solve Sudoku are formulated as an energy function in the same form as a Q’tron NN’s. The Q’tron NN for Sudoku can then be built simply by mapping. Equipping the NN with the proposed noise-injection mechanism, the Sudoku NN is ensured local-minima free. Besides solving Sudoku puzzles, the NN can also be used to generate Sudoku puzzles.