Linear-space best-first search
Artificial Intelligence
Performance of linear-space search algorithms
Artificial Intelligence
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Constraint Processing
Distributed Sensor Networks: A Multiagent Perspective
Distributed Sensor Networks: A Multiagent Perspective
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
Preprocessing techniques for accelerating the DCOP algorithm ADOPT
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Multiply-constrained distributed constraint optimization
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
Hierarchical variable ordering for distributed constraint optimization
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A complete distributed constraint optimization method for non-traditional pseudotree arrangements
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
SSDPOP: improving the privacy of DCOP with secret sharing
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Evaluating the performance of DCOP algorithms in a real world, dynamic problem
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
On k-optimal distributed constraint optimization algorithms: new bounds and algorithms
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Trading off solution cost for smaller runtime in DCOP search algorithms
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
ADOPT-ing: unifying asynchronous distributed optimization with asynchronous backtracking
Autonomous Agents and Multi-Agent Systems
Caching schemes for DCOP search algorithms
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Distributed constraint optimization with structured resource constraints
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Directed soft arc consistency in pseudo trees
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
An overview of privacy improvements to k-optimal DCOP algorithms
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Efficient Handling of Complex Local Problems in Distributed Constraint Optimization
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
ODPOP: an algorithm for open/distributed constraint optimization
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
AND/OR Branch-and-Bound search for combinatorial optimization in graphical models
Artificial Intelligence
Best-first AND/OR search for graphical models
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Anytime local search for distributed constraint optimization
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Asynchronous forward bounding for distributed COPs
Journal of Artificial Intelligence Research
Taking advantage of stable sets of variables in constraint satisfaction problems
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
Quality guarantees on k-optimal solutions for distributed constraint optimization problems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On the space-time trade-off in solving constraint satisfaction problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Distributed Constraint Optimization for Large Teams of Mobile Sensing Agents
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Decentralised coordination of mobile sensors using the max-sum algorithm
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Dynamic configuration of agent organizations
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Incremental DCOP search algorithms for solving dynamic DCOPs
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Generalizing ADOPT and BnB-ADOPT
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Distributed constraint optimization problems related with soft arc consistency
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Anytime AND/OR depth-first search for combinatorial optimization
AI Communications - The Symposium on Combinatorial Search
Concurrent forward bounding for distributed constraint optimization problems
Artificial Intelligence
Including soft global constraints in DCOPs
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
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
Target to sensor allocation: A hierarchical dynamic Distributed Constraint Optimization approach
Computer Communications
Maintaining soft arc consistencies in BnB-ADOPT+ during search
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Distributed reasoning for multiagent simple temporal problems
Journal of Artificial Intelligence Research
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
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Distributed constraint optimization (DCOP) problems are a popular way of formulating and solving agent-coordination problems. A DCOP problem is a problem where several agents coordinate their values such that the sum of the resulting constraint costs is minimal. It is often desirable to solve DCOP problems with memory-bounded and asynchronous algorithms. We introduce Branch-and-Bound ADOPT (BnB-ADOPT), a memory-bounded asynchronous DCOP search algorithm that uses the message-passing and communication framework of ADOPT (Modi, Shen, Tambe, & Yokoo, 2005), a well known memory-bounded asynchronous DCOP search algorithm, but changes the search strategy of ADOPT from best-first search to depth-first branch-and-bound search. Our experimental results show that BnB-ADOPT finds cost-minimal solutions up to one order of magnitude faster than ADOPT for a variety of large DCOP problems and is as fast as NCBB, a memory-bounded synchronous DCOP search algorithm, for most of these DCOP problems. Additionally, it is often desirable to find bounded-error solutions for DCOP problems within a reasonable amount of time since finding cost-minimal solutions is NP-hard. The existing bounded-error approximation mechanism allows users only to specify an absolute error bound on the solution cost but a relative error bound is often more intuitive. Thus, we present two new bounded-error approximation mechanisms that allow for relative error bounds and implement them on top of BnB-ADOPT.