Enforcing Soft Local Consistency on Multiple Representations for DCOP Solving
نویسندگان
چکیده
Connecting soft arc consistency with distributed search in DCOP solving has been very beneficial for performance. However, including higher levels of soft arc consistency breaks usual privacy requirements. To avoid this issue, we propose to keep different representations of the same problem on each agent, on which soft arc consistencies are enforced respecting privacy. Deletions caused in one representation can be legally propagated to others. Experimentally, this causes significant benefits.
منابع مشابه
Improving BnB-ADOPT+-AC
Several multiagent tasks can be formulated and solved as DCOPs. BnB-ADOPT-AC is one of the most efficient algorithms for optimal DCOP solving. It is based on BnBADOPT, removing redundant messages and maintaining soft arc consistency during search. In this paper, we present several improvements for this algorithm, namely (i) a better implementation, (ii) processing exactly simultaneous deletions...
متن کاملMaintaining Soft Arc Consistencies in BnB-ADOPT+ During Search
Distributed Constraint Optimization Problems (DCOPs) have been applied in modeling and solving many multiagent coordination problems, such as meeting scheduling, sensor networks and traffic control. Several distributed algorithms for optimal DCOP solving have been proposed: ADOPT [Modi et al., 2005], DPOP [Petcu and Faltings, 2005], BnB-ADOPT [Yeoh et al., 2010]. BnB-ADOPT-AC and BnB-ADOPTFDAC ...
متن کاملA Novel Way to Connect BnB-ADOPT+, with Soft AC
Combining BnB-ADOPT$^+$ with AC and FDAC levels of soft arc consistency (SAC) improves efficiency for optimal DCOP solving. However, it seems difficult in distributed context to achieve the higher consistency level EDAC, especially considering privacy. As alternative, we propose DAC by token passing. Agents receiving a token ask neighbors for cost extensions. When deletions or $C_phi$ increment...
متن کاملA Novel Way to Connect BnB-ADOPT+ with Soft AC
Combining BnB-ADOPT$^+$ with AC and FDAC levels of soft arc consistency (SAC) improves efficiency for optimal DCOP solving. However, it seems difficult in distributed context to achieve the higher consistency level EDAC, especially considering privacy. As alternative, we propose DAC by token passing. Agents receiving a token ask neighbors for cost extensions. When deletions or $C_phi$ increment...
متن کاملExploiting Tree Decomposition and Soft Local Consistency In Weighted CSP
Several recent approaches for processing graphical models (constraint and Bayesian networks) simultaneously exploit graph decomposition and local consistency enforcing. Graph decomposition exploits the problem structure and offers space and time complexity bounds while hard information propagation provides practical improvements of space and time behavior inside these theoretical bounds. Concur...
متن کامل