A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
A comparison of structural CSP decomposition methods
Artificial Intelligence
The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
IEEE Transactions on Knowledge and Data Engineering
Efficient Subgraph Isomorphism Detection: A Decomposition Approach
IEEE Transactions on Knowledge and Data Engineering
Adaptive Teamwork Coordination Using Graph Matching over Hierarchical Intentional Structures
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
Impact of problem centralization in distributed constraint optimization algorithms
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Solving set constraint satisfaction problems using ROBDDs
Journal of Artificial Intelligence Research
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
| Hi-index | 0.00 |
In this paper, we propose a novel approach to solving the distributed constraint optimisation problem (DCOP) that guarantees completeness, while having linear communication complexity. The key to performance advantages, in terms of both computation and communication, derives from the application of the repeatedly-half principle to manage complexity by a combination of problem distribution through graph decomposition and multi-stage solution quality propagation. Experimental result shows that our new algorithm is faster than a recent competitive distributed algorithm for solving MaxSAT graph colouring problems. It also indicates the potential for the decomposition approach over a centralised method based on the same search strategy, and is consistent with recent results on domain propagation and structural decomposition in the CSP literature.