Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
An introduction to distributed algorithms
An introduction to distributed algorithms
Heuristic Algorithms for the Triangulation of Graphs
IPMU'94 Selected papers from the 5th International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems, Advances in Intelligent Computing
Efficient Approximation for Triangulation of Minimum Treewidth
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Constraint Processing
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
Design and Analysis of Distributed Algorithms (Wiley Series on Parallel and Distributed Computing)
Design and Analysis of Distributed Algorithms (Wiley Series on Parallel and Distributed Computing)
A complete distributed constraint optimization method for non-traditional pseudotree arrangements
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
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
Generalizing DPOP: Action-GDL, a new complete algorithm for DCOPs
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
IDB-ADOPT: A Depth-First Search DCOP Algorithm
Recent Advances in Constraints
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Incremental compilation of bayesian networks
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
The generalized distributive law
IEEE Transactions on Information Theory
Bounded approximate decentralised coordination via the max-sum algorithm
Artificial Intelligence
Communication-constrained DCOPs: message approximation in GDL with function filtering
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Multi-agent coordination: dcops and beyond
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Stochastic dominance in stochastic DCOPs for risk-sensitive applications
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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
Distributed Gibbs: a memory-bounded sampling-based DCOP algorithm
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Improved max-sum algorithm for DCOP with n-ary constraints
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Protecting privacy through distributed computation in multi-agent decision making
Journal of Artificial Intelligence Research
Agent-based decentralised coordination for sensor networks using the max-sum algorithm
Autonomous Agents and Multi-Agent Systems
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In this paper we propose a novel message-passing algorithm, the so-called Action-GDL, as an extension to the generalized distributive law (GDL) to efficiently solve DCOPs. Action-GDL provides a unifying perspective of several dynamic programming DCOP algorithms that are based on GDL, such as DPOP and DCPOP algorithms. We empirically show how Action-GDL using a novel distributed post-processing heuristic can outperform DCPOP, and by extension DPOP, even when the latter uses the best arrangement provided by multiple state-of-the-art heuristics.