Support-based distributed search: a new approach for multiagent constraint processing
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
No-commitment branch and bound search for distributed constraint optimization
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Decentralised coordination of continuously valued control parameters using the max-sum algorithm
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Superstabilizing, fault-containing distributed combinatorial optimization
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Asynchronous algorithms for approximate distributed constraint optimization with quality bounds
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Divide-and-coordinate: DCOPs by agreement
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Using distributed agents for patient scheduling
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
Target to sensor allocation: A hierarchical dynamic Distributed Constraint Optimization approach
Computer Communications
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Dynamic distributed constraint optimisation problems are a very effective tool for solving multi-agent problems. However they require protocols for agents to collaborate in optimising shared objectives in a decentralised manner without necessarily revealing all of their private constraints. In this paper, we present the details of the Support-Based Distributed Optimisation (SBDO) algorithm for solving dynamic distributed constraint optimisation problems. This algorithm is complete wrt hard constraints but not wrt objectives. Furthermore, we show that SBDO is completely asynchronous, sound and fault tolerant. Finally, we evaluate the performance of SDBO with respect to DynCOAA for DynDCOP and ADOPT, DPOP for DCOP. The results highlight that in general, SBDO out performs these algorithms on criteria such as time, solution quality, number of messages, non-concurrent constraint checks and memory usage.