Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Constraint Processing
Dynamic prioritization of complex agents in distributed constraint satisfaction problems
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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A constraint satisfaction problem (CSP) is a general framework that can formalize various application problems in artificial intelligence. However, practical real-world problems tend to be over-constrained, and the descriptive power of the CSP is not always sufficient in formulating the problems because of various constraints involved. In this paper, we will focus on an important subclass of distributed partial CSPs called the distributed maximal CSPs that can be applied to more practical kinds of problems. Specifically, we propose a hybrid-type algorithm of solving distributed maximal CSPs using a combination of approximate and exact algorithms that yields faster optimum solutions than conventional methods. Experimental results are presented that demonstrate the effectiveness of the proposed approach.