Simple support-based distributed search

Authors:
Peter Harvey;Chee Fon Chang;Aditya Ghose
Affiliations:
Decision Systems Laboratory, School of IT and Computer Science, University of Wollongong, Australia;Decision Systems Laboratory, School of IT and Computer Science, University of Wollongong, Australia;Decision Systems Laboratory, School of IT and Computer Science, University of Wollongong, Australia
Venue:
AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
Year:
2006

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Abstract

Distributed Constraint Satisfaction Problems provide a natural mechanism for multiagent coordination and agreement. To date, algorithms for Distributed Constraint Satisfaction Problems have tended to mirror existing non-distributed global-search or local-search algorithms. Unfortunately, existing distributed global-search algorithms derive from classical backtracking search methods and require a total ordering over agents for completeness. Distributed variants of local-search algorithms (such as distributed breakout) inherit the incompleteness properties of their predecessors, or depend on the creation of new communication links between agents. In [5, 4] a new algorithm was presented designed explicitly for distributed environments so that a global ordering is not required, while avoiding the problems of existing local-search algorithms. This paper presents a significant improvement on that algorithm in performance and provability.