Graphical models for interactive POMDPs: representations and solutions
Autonomous Agents and Multi-Agent Systems
Partially-synchronized DEC-MDPs in dynamic mechanism design
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Graphical model inference in optimal control of stochastic multi-agent systems
Journal of Artificial Intelligence Research
Communication-based decomposition mechanisms for decentralized MDPs
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
Introduction to planning in multiagent systems
Multiagent and Grid Systems - Planning in multiagent systems
Seeing the forest despite the trees: large scale spatial-temporal decision making
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
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
Online planning for multi-agent systems with bounded communication
Artificial Intelligence
Decentralized MDPs with sparse interactions
Artificial Intelligence
Toward error-bounded algorithms for infinite-horizon DEC-POMDPs
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Teamwork in distributed POMDPs: execution-time coordination under model uncertainty
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
On the power of global reward signals in reinforcement learning
MATES'11 Proceedings of the 9th German conference on Multiagent system technologies
Towards Addressing Model Uncertainty: Robust Execution-Time Coordination for Teamwork
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Autonomous Agents and Multi-Agent Systems
Online planning for ad hoc autonomous agent teams
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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
Exploiting model equivalences for solving interactive dynamic influence diagrams
Journal of Artificial Intelligence Research
QueryPOMDP: POMDP-based communication in multiagent systems
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
Producing efficient error-bounded solutions for transition independent decentralized mdps
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Approximate solutions for factored Dec-POMDPs with many agents
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Decentralized multi-robot cooperation with auctioned POMDPs
International Journal of Robotics Research
Incremental clustering and expansion for faster optimal planning in decentralized POMDPs
Journal of Artificial Intelligence Research
Sufficient plan-time statistics for decentralized POMDPs
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Over the last 5 years, the AI community has shown considerable interest in decentralized control of multiple decision makers or "agents" under uncertainty. This problem arises in many application domains, such as multi-robot coordination, manufacturing, information gathering, and load balancing. Such problems must be treated as decentralized decision problems because each agent may have different partial information about the other agents and about the state of the world. It has been shown that these problems are significantly harder than their centralized counterparts, requiring new formal models and algorithms to be developed. Rapid progress in recent years has produced a number of different frameworks, complexity results, and planning algorithms. The objectives of this paper are to provide a comprehensive overview of these results, to compare and contrast the existing frameworks, and to provide a deeper understanding of their relationships with one another, their strengths, and their weaknesses. While we focus on cooperative systems, we do point out important connections with game-theoretic approaches. We analyze five different formal frameworks, three different optimal algorithms, as well as a series of approximation techniques. The paper provides interesting insights into the structure of decentralized problems, the expressiveness of the various models, and the relative advantages and limitations of the different solution techniques. A better understanding of these issues will facilitate further progress in the field and help resolve several open problems that we identify.