Solving DisCSPs with Penalty Driven Search

Muhammed Basharu, Ines Arana, Hatem Ahriz

We introduce the Distributed, Penalty-driven Local search algorithm (DisPeL) for solving Distributed Constraint Satisfaction Problems. DisPeL is a novel distributed iterative improvement algorithm which escapes local optima by the use of both temporary and incremental penalties and a tabu-like no-good store. We justify the use of these features and provide empirical results which demonstrate the competitiveness of the algorithm.

Content Area: 1. Agents/Multiagent Systems

Subjects: 15.2 Constraint Satisfaction; 7. Distributed AI

Submitted: May 10, 2005


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