Self-stabilizing systems in spite of distributed control
Communications of the ACM
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed Algorithms
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
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
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
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
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Concurrent search for distributed CSPs
Artificial Intelligence
Nogood based asynchronous distributed optimization (ADOPT ng)
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Message delay and DisCSP search algorithms
Annals of Mathematics and Artificial Intelligence
Asynchronous Forward-checking for DisCSPs
Constraints
SSDPOP: improving the privacy of DCOP with secret sharing
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Distributed Log-based Reconciliation
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Superstabilizing, fault-containing distributed combinatorial optimization
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Conflict directed backjumping for Max-CSPs
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
Local search for distributed asymmetric optimization
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm
Journal of Artificial Intelligence Research
Bounded approximate decentralised coordination via the max-sum algorithm
Artificial Intelligence
Distributed constraint programming with agents
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
Max/min-sum distributed constraint optimization through value propagation on an alternating DAG
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Partial cooperation in multi-agent search
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Concurrent forward bounding for distributed constraint optimization problems
Artificial Intelligence
Removing redundant messages in N-ary BnB-ADOPT
Journal of Artificial Intelligence Research
Distributed Gibbs: a memory-bounded sampling-based DCOP algorithm
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Asymmetric distributed constraint optimization problems
Journal of Artificial Intelligence Research
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A new search algorithm for solving distributed constraint optimization problems (DisCOPs) is presented. Agents assign variables sequentially and compute bounds on partial assignments asynchronously. The asynchronous bounds computation is based on the propagation of partial assignments. The asynchronous forward-bounding algorithm (AFB) is a distributed optimization search algorithm that keeps one consistent partial assignment at all times. The algorithm is described in detail and its correctness proven. Experimental evaluation shows that AFB outperforms synchronous branch and bound by many orders of magnitude, and produces a phase transition as the tightness of the problem increases. This is an analogous effect to the phase transition that has been observed when local consistency maintenance is applied to MaxCSPs. The AFB algorithm is further enhanced by the addition of a backjumping mechanism, resulting in the AFB-BJ algorithm. Distributed backjumping is based on accumulated information on bounds of all values and on processing concurrently a queue of candidate goals for the next move back. The AFB-BJ algorithm is compared experimentally to other DisCOP algorithms (ADOPT, DPOP, OptAPO) and is shown to be a very efficient algorithm for DisCOPs.