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Y. Zhang and Alan K. Mackworth. Parallel and Distributed Constraint Satisfaction. In Proceedings of the Workshop on Parallel Processing in Artificial Intelligence, pp. 229–234, Sydney, Australia, August 1991.
A parallel distributed framework to solve constraint satisfaction problems based on connectionist ideas of distributed information processing is presented. In this approach, each variable of a given problem is associated with a simple agent continuously applying a variable manipulation rule in the spirit of local conflict minimization to satisfy all constraints this variable is involved in. All agents are working simultaneously forming together a recurrent dynamical system which should selforganize after some iterations to a feasible problem solution. We investigate whether and how manipulation rules can be chosen such that the whole process converges without coordinating agent activities.
@InProceedings{PPAI91,
author = {Y. Zhang and Alan K. Mackworth},
title = {Parallel and Distributed Constraint Satisfaction},
year = {1991},
month = {August},
booktitle = {Proceedings of the Workshop on Parallel Processing in Artificial Intelligence},
address = {Sydney, Australia}
pages = {229--234},
abstract = {A parallel distributed framework to solve constraint satisfaction problems based on connectionist ideas of distributed information processing is presented. In this approach, each variable of a given problem is associated with a simple agent continuously applying a variable manipulation rule in the spirit of local conflict minimization to satisfy all constraints this variable is involved in. All agents are working simultaneously forming together a recurrent dynamical system which should selforganize after some iterations to a feasible problem solution. We investigate whether and how manipulation rules can be chosen such that the whole process converges without coordinating agent activities.},
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}
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