The Complexity of Decentralized Control of Markov Decision Processes
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
The complexity of multiagent systems: the price of silence
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Dynamic programming for partially observable stochastic games
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Point-based dynamic programming for DEC-POMDPs
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
A particle filtering based approach to approximating interactive POMDPs
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
The communicative multiagent team decision problem: analyzing teamwork theories and models
Journal of Artificial Intelligence Research
Solving transition independent decentralized Markov decision processes
Journal of Artificial Intelligence Research
A framework for sequential planning in multi-agent settings
Journal of Artificial Intelligence Research
Taming decentralized POMDPs: towards efficient policy computation for multiagent settings
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Bounded policy iteration for decentralized POMDPs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Value-based observation compression for DEC-POMDPs
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Constraint-based dynamic programming for decentralized POMDPs with structured interactions
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Point-based incremental pruning heuristic for solving finite-horizon DEC-POMDPs
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Lossless clustering of histories in decentralized POMDPs
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Achieving goals in decentralized POMDPs
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Improved approximation of interactive dynamic influence diagrams using discriminative model updates
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Anytime coordination using separable bilinear programs
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Communication-based decomposition mechanisms for decentralized MDPs
Journal of Artificial Intelligence Research
Optimal and approximate Q-value functions for decentralized POMDPs
Journal of Artificial Intelligence Research
Policy iteration for decentralized control of Markov decision processes
Journal of Artificial Intelligence Research
Monte Carlo sampling methods for approximating interactive POMDPs
Journal of Artificial Intelligence Research
Agent Influence and Intelligent Approximation in Multiagent Problems
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
A bilinear programming approach for multiagent planning
Journal of Artificial Intelligence Research
Heuristic search for identical payoff Bayesian games
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Point-based policy generation for decentralized POMDPs
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Point-based backup for decentralized POMDPs: complexity and new algorithms
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Optimizing fixed-size stochastic controllers for POMDPs and decentralized POMDPs
Autonomous Agents and Multi-Agent Systems
An investigation into mathematical programming for finite horizon decentralized POMDPs
Journal of Artificial Intelligence Research
Point-based bounded policy iteration for decentralized POMDPs
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Online planning for multi-agent systems with bounded communication
Artificial Intelligence
Solving efficiently Decentralized MDPs with temporal and resource constraints
Autonomous Agents and Multi-Agent Systems
Exploiting symmetries for single- and multi-agent Partially Observable Stochastic Domains
Artificial Intelligence
Scaling up optimal heuristic search in Dec-POMDPs via incremental expansion
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Heuristic search of multiagent influence space
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Exploiting model equivalences for solving interactive dynamic influence diagrams
Journal of Artificial Intelligence Research
People, sensors, decisions: Customizable and adaptive technologies for assistance in healthcare
ACM Transactions on Interactive Intelligent Systems (TiiS) - Special issue on highlights of the decade in interactive intelligent systems
Modeling information exchange opportunities for effective human-computer teamwork
Artificial Intelligence
Solving decentralized POMDP problems using genetic algorithms
Autonomous Agents and Multi-Agent Systems
Incremental clustering and expansion for faster optimal planning in decentralized POMDPs
Journal of Artificial Intelligence Research
Monte-Carlo expectation maximization for decentralized POMDPs
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicability and scalability of planning algorithms is an important challenge. We present the first memory-bounded dynamic programming algorithm for finite-horizon decentralized POMDPs. A set of heuristics is used to identify relevant points of the infinitely large belief space. Using these belief points, the algorithm successively selects the best joint policies for each horizon. The algorithm is extremely efficient, having linear time and space complexity with respect to the horizon length. Experimental results show that it can handle horizons that are multiple orders of magnitude larger than what was previously possible, while achieving the same or better solution quality. These results significantly increase the applicability of decentralized decision-making techniques.