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Abstract:
Constraint satisfaction problems are important in AI. Various distributed and parallel computing strategies have been proposed to solve these problems. In this paper, these strategies are classified as distributed-agent-based, parallel-agent-based, and function-agent-based distributed problem-solving strategies. These different strategies are presented and discussed. Parallel-agentbased strategies are found to be very versatile. Computational experience is presented.