Reinforcement Learning
Exact and approximate algorithms for partially observable markov decision processes
Exact and approximate algorithms for partially observable markov decision processes
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
Heuristic search value iteration for POMDPs
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Exploiting structure to efficiently solve large scale partially observable markov decision processes
Exploiting structure to efficiently solve large scale partially observable markov decision processes
Not all agents are equal: scaling up distributed POMDPs for agent networks
Proceedings of the 7th 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
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Solving transition independent decentralized Markov decision processes
Journal of Artificial Intelligence Research
Perseus: randomized point-based value iteration for POMDPs
Journal of Artificial Intelligence Research
Policy iteration for decentralized control of Markov decision processes
Journal of Artificial Intelligence Research
Average-reward decentralized Markov decision processes
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Memory-bounded dynamic programming for DEC-POMDPs
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Solving POMDPs using quadratically constrained linear programs
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Taming decentralized POMDPs: towards efficient policy computation for multiagent settings
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Point-based value iteration: an anytime algorithm for POMDPs
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
Probabilistic robot navigation in partially observable environments
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Solving POMDPs by searching the space of finite policies
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Solving POMDPs by searching in policy space
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
An optimal best-first search algorithm for solving infinite horizon DEC-POMDPs
ECML'05 Proceedings of the 16th European conference on Machine Learning
Point-based policy generation for decentralized POMDPs
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Principled method for exploiting opening books
CG'10 Proceedings of the 7th international conference on Computers and games
Influence diagrams with memory states: representation and algorithms
ADT'11 Proceedings of the Second international conference on Algorithmic decision theory
A simple metric for turn-taking in emergent communication
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Scalable multiagent planning using probabilistic inference
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Solving decentralized POMDP problems using genetic algorithms
Autonomous Agents and Multi-Agent Systems
Applying POMDP to moving target optimization
Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop
A bayesian approach for constrained multi-agent minimum time search in uncertain dynamic domains
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Producing efficient error-bounded solutions for transition independent decentralized mdps
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Incremental clustering and expansion for faster optimal planning in decentralized POMDPs
Journal of Artificial Intelligence Research
Isomorph-free branch and bound search for finite state controllers
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their high computational complexity, however, presents an important research challenge. One way to address the intractable memory requirements of current algorithms is based on representing agent policies as finite-state controllers. Using this representation, we propose a new approach that formulates the problem as a nonlinear program, which defines an optimal policy of a desired size for each agent. This new formulation allows a wide range of powerful nonlinear programming algorithms to be used to solve POMDPs and DEC-POMDPs. Although solving the NLP optimally is often intractable, the results we obtain using an off-the-shelf optimization method are competitive with state-of-the-art POMDP algorithms and outperform state-of-the-art DEC-POMDP algorithms. Our approach is easy to implement and it opens up promising research directions for solving POMDPs and DEC-POMDPs using nonlinear programming methods.