A Hybrid Approach to Distributed Constraint Satisfaction

Authors:
David Lee;Inés Arana;Hatem Ahriz;Kit-Ying Hui
Affiliations:
School of Computing, The Robert Gordon University, Aberdeen, United Kingdom;School of Computing, The Robert Gordon University, Aberdeen, United Kingdom;School of Computing, The Robert Gordon University, Aberdeen, United Kingdom;School of Computing, The Robert Gordon University, Aberdeen, United Kingdom
Venue:
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Year:
2008

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Abstract

We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we propose the hybrid algorithm PenDHyb where the distributed local search algorithm DisPeL is run for a very small amount of time in order to learn about the difficult areas of the problem from the penalty counts imposed during its problem-solving. This knowledge is then used to guide the systematic search algorithm SynCBJ. Extensive empirical results in several problem classes indicate that PenDHyb is effective for large problems.