Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
IEEE Transactions on Knowledge and Data Engineering
Asynchronous Weak-commitment Search for Solving Distributed Constraint Satisfaction Problems
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
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
A mediation-based approach to cooperative, distributed problem solving
A mediation-based approach to cooperative, distributed problem solving
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
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
Examining DCSP coordination tradeoffs
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
CompAPO: A Complete Version of the APO Algorithm
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Asynchronous Forward-Bounding for Distributed Constraints Optimization
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Journal of Artificial Intelligence Research
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
MaxCAPO: a new expansion of APO to solve distributed constraint satisfaction problems
ASC '07 Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing
Min-domain ordering for asynchronous backtracking
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Asynchronous partitioning framework
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Solving distributed CSPs using dynamic, partial centralization without explicit constraint passing
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
Concurrent forward bounding for distributed constraint optimization problems
Artificial Intelligence
Improving Asynchronous Partial Overlay
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Asymmetric distributed constraint optimization problems
Journal of Artificial Intelligence Research
Protecting privacy through distributed computation in multi-agent decision making
Journal of Artificial Intelligence Research
Improving the privacy of the asynchronous partial overlay protocol
Multiagent and Grid Systems - Principles and Practice of Multi-Agent Systems
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Asynchronous Partial Overlay (APO) is a search algorithm that uses cooperative mediation to solve Distributed Constraint Satisfaction Problems (DisCSPs). The algorithm partitions the search into different subproblems of the DisCSP. The original proof of completeness of the APO algorithm is based on the growth of the size of the subproblems. The present paper demonstrates that this expected growth of subproblems does not occur in some situations, leading to a termination problem of the algorithm. The problematic parts in the APO algorithm that interfere with its completeness are identified and necessary modifications to the algorithm that fix these problematic parts are given. The resulting version of the algorithm, Complete Asynchronous Partial Overlay (CompAPO), ensures its completeness. Formal proofs for the soundness and completeness of CompAPO are given. A detailed performance evaluation of CompAPO comparing it to other DisCSP algorithms is presented, along with an extensive experimental evaluation of the algorithm's unique behavior. Additionally, an optimization version of the algorithm, CompOptAPO, is presented, discussed, and evaluated.