Nogood Recording for Valued Constraint Satisfaction Problems
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
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
Bumping strategies for the multiagent agreement problem
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Preprocessing techniques for accelerating the DCOP algorithm ADOPT
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Asynchronous backtracking without adding links: a new member in the ABT family
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Asynchronous aggregation and consistency in distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Nogood based asynchronous distributed optimization (ADOPT ng)
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Experimental analysis of privacy loss in DCOP algorithms
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
ODPOP: an algorithm for open/distributed constraint optimization
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
PC-DPOP: a new partial centralization algorithm for distributed optimization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Concurrent forward bounding for distributed constraint optimization problems
Artificial Intelligence
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Several distributed constraint reasoning algorithms employ Depth First Search (DFS) trees on the constraint graph that spans involved agents. In this article we show that it is possible to dynamically detect a minimal DFS tree, compatible with the current order on agents, during the distributed constraint reasoning process of the ADOPT algorithm. This also allows for shorter DFS trees during the initial steps of the algorithms, while some constraints did not yet prove useful given visited combinations of assignments. Earlier distributed algorithms for finding spanning trees on agents did not look to maintain compatibility with an order already used. We also show that announcing a nogood to a single optional agent is bringing significant improvements in the total number of messages. The dynamic detection of the DFS tree brings improvements in simulated time.