An asynchronous complete method for distributed constraint optimization
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Constraint Processing
Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
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
Impact of problem centralization in distributed constraint optimization algorithms
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Unifying tree decompositions for reasoning in graphical models
Artificial Intelligence
Autonomous Agents and Multi-Agent Systems
MDPOP: faithful distributed implementation of efficient social choice problems
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Journal of Artificial Intelligence Research
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
AND/OR branch-and-bound for graphical models
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Sensitivity analysis for distributed optimization with resource constraints
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Analyzing the performance of distributed algorithms
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Multiagent Communication Security in Adversarial Settings
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Effective Variants of the Max-Sum Algorithm for Radar Coordination and Scheduling
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Distributed constraint optimization with MULBS: A case study on collaborative meeting scheduling
Journal of Network and Computer Applications
Stochastic dominance in stochastic DCOPs for risk-sensitive applications
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Dynamic multiagent load balancing using distributed constraint optimization techniques
Web Intelligence and Agent Systems
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Fully decentralized algorithms for distributed constraint optimization often require excessive amounts of communication when applied to complex problems. The OptAPO algorithm of [Mailler and Lesser, 2004] uses a strategy of partial centralization to mitigate this problem. We introduce PC-DPOP, a new partial centralization technique, based on the DPOP algorithm of [Petcu and Faltings, 2005]. PC-DPOP provides better control over what parts of the problem are centralized and allows this centralization to be optimal with respect to the chosen communication structure. Unlike OptAPO, PC-DPOP allows for a priory, exact predictions about privacy loss, communication, memory and computational requirements on all nodes and links in the network. Upper bounds on communication and memory requirements can be specified. We also report strong efficiency gains over OptAPO in experiments on three problem domains.