An information-based neural approach to generic constraint satisfaction
نویسندگان
چکیده
منابع مشابه
An information-based neural approach to generic constraint satisfaction
A novel artificial neural network heuristic (INN) for general constraint satisfaction problems is presented, extending a recently suggested method restricted to boolean variables. In contrast to conventional ANN methods, it employs a particular type of non-polynomial cost function, based on the information balance between variables and constraints in a mean-field setting. Implemented as an anne...
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A novel artificial neural network approach to constraint satisfaction problems is presented. Based on information-theoretical considerations, it differs from a conventional mean-field approach in the form of the resulting free energy. The method, implemented as an annealing algorithm, is numerically explored on a testbed of K-SAT problems. The performance shows a dramatic improvement over that ...
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A novel artificial neural network heuristic (INN) for general constraint satisfaction problems is presented, extending a recently suggested method restricted to boolean variables. In contrast to conventional ANN methods, it employs a particular type of non-polynomial cost function, based on the information balance between variables and constraints in a mean-field setting. Implemented as an anne...
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A novel artiicial neural network heuristic (INN) for general constraint satisfaction problems is presented, extending a recently suggested method for binary problems. It employs a particular non-polynomial cost function, based on the information balance between multi-state Potts variables and constraints. Implemented as an annealing algorithm, the method is numerically explored on a testbed of ...
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A novel artiicial neural network approach to constraint satisfaction problems is presented. Based on information-theoretical considerations, it diiers from a conventional mean-eld approach in the form of the resulting free energy. The method, implemented as an annealing algorithm, is numerically explored on a testbed of K-SAT problems. The performance shows a dramatic improvement to that of a c...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2002
ISSN: 0004-3702
DOI: 10.1016/s0004-3702(02)00291-6