Tree clustering for constraint networks (research note)
Artificial Intelligence
On the Desirability of Acyclic Database Schemes
Journal of the ACM (JACM)
Algorithms for a temporal decoupling problem in multi-agent planning
Eighteenth national conference on Artificial intelligence
Constraint Processing
A domain decomposition algorithm for constraint satisfaction
Journal of Experimental Algorithmics (JEA)
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
A comparison of structural CSP decomposition methods
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Constraint partitioning in penalty formulations for solving temporal planning problems
Artificial Intelligence
Optimal temporal decoupling in multiagent systems
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
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In constraint satisfaction, decomposition is a common technique to split a problem in a number of parts in such a way that the global solution can be efficiently assembled from the solutions of the parts. In this paper, we study the decomposition problem from an autonomous agent perspective. Here, a constraint problem has to be solved by different agents each controlling a disjoint set of variables. Such a problem is called concurrently decomposable if each agent is (i) capable to solve its own part of the problem independently of the others, and (ii) the individual solutions always can be merged to a complete solution of the total problem. First of all, we investigate how difficult it is to decide whether or not a given constraint system and agent partitioning allows for such a concurrent decomposition. Secondly, we investigate how difficult it is to find suitable reformulations of the original constraint problem that allow for concurrent decomposition.