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Stochastic networks for constraint satisfaction and optimization

Sastry, PS (1990) Stochastic networks for constraint satisfaction and optimization. In: Sadhana, 15 (4-5). pp. 251-262.

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Stochastic algorithms for solving constraint satisfaction problems with soft constraints that can be implemented on a parallel distributed network are discussed in a unified framework. The algorithms considered are: the Boltzmann machine, a Learning Automata network for Relaxation Labelling and a formulation of optimization problems based on Markov random field (MRF) models. It is shown that the automata network and the MRF formulation can be regarded as generalisations of the Boltzmann machine in different directions.

Item Type: Journal Article
Publication: Sadhana
Publisher: Indian Academy of Sciences
Additional Information: Copyright of this article belongs to Indian Academy of Sciences.
Keywords: Neural networks; Boltzmann machine; learning automata; consistent labelling problem
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 06 Mar 2008
Last Modified: 19 Sep 2010 04:43
URI: http://eprints.iisc.ac.in/id/eprint/13307

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