Solving Distributed Constraint Optimization Problems Using Cooperative Mediation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
ADOPT-ing: unifying asynchronous distributed optimization with asynchronous backtracking
Autonomous Agents and Multi-Agent Systems
Caching schemes for DCOP search algorithms
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
ODPOP: an algorithm for open/distributed constraint optimization
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
MB-DPOP: a new memory-bounded algorithm for distributed optimization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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Distributed search is an important processing to solve problems in distributed cooperative systems. As fundamental research of distributed cooperative problem solving, distributed constraint optimization problems (DCOPs) have been studied. For the DCOPs, exact distributed search algorithms that are based on pseudotrees have been proposed. In the search algorithms, tree-searches and dynamic programming methods are performed using an order of variables defined by the pseudo-trees. However, analyzing the behaviors of search algorithms is relatively difficult due to the distributed processing. In this study, we show a representation of the essential computation contained in search algorithms based on pseudo-trees. Using the representations of the computation, a basic algorithm that contains a relatively clear data-flow of the processing is composed. This representation can be considered a basis of analyzing the dependency of the processing and deriving actual distributed algorithms.