Box Puzzling Problem Solver by Hysteresis Neural Networks

Toshiya NAKAGUCHI  Shinya ISOME  Kenya JIN'NO  Mamoru TANAKA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E84-A   No.9   pp.2173-2181
Publication Date: 2001/09/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)
Category: Application of Neural Network
Keyword: 
nonlinear dynamics,  hysteresis neural networks,  combinatorial optimization problems,  constraint satisfaction problems,  box puzzling problem,  

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Summary: 
We propose hysteresis neural network solving combinatorial optimization problems, Box Puzzling Problem. Hysteresis neural network searches solutions of the problem with nonlinear dynamics. The output vector becomes stable only when it corresponds with a solution. This system does never become stable without satisfying constraints of the problem. After estimating hardware calculating time, we obtain that numerical calculating time increases extremely comparing with hardware time as problem's scale increases. However the system has possibility of limit cycle. Though it is very hard to remove limit cycle completely, we propose some methods to remove this phenomenon.