Algebraic decision diagrams and their applications
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Planning and acting in partially observable stochastic domains
Artificial Intelligence
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
Probabilistic planning for robotic exploration
Probabilistic planning for robotic exploration
Value-function approximations for partially observable Markov decision processes
Journal of Artificial Intelligence Research
Perseus: randomized point-based value iteration for POMDPs
Journal of Artificial Intelligence Research
Computing optimal policies for partially observable decision processes using compact representations
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Tractable inference for complex stochastic processes
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Incremental pruning: a simple, fast, exact method for partially observable Markov decision processes
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Planning under Uncertainty for Robotic Tasks with Mixed Observability
International Journal of Robotics Research
Adaptive decision support for structured organizations: a case for OrgPOMDPs
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Decision Support in Organizations: A Case for OrgPOMDPs
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Recognizing internal states of other agents to anticipate and coordinate interactions
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
A survey of point-based POMDP solvers
Autonomous Agents and Multi-Agent Systems
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We propose Symbolic heuristic search value iteration (Symbolic HSVI) algorithm, which extends the heuristic search value iteration (HSVI) algorithm in order to handle factored partially observable Markov decision processes (factored POMDPs). The idea is to use algebraic decision diagrams (ADDs) for compactly representing the problem itself and all the relevant intermediate computation results in the algorithm. We leverage Symbolic Perseus for computing the lower bound of the optimal value function using ADD operators, and provide a novel ADD-based procedure for computing the upper bound. Experiments on a number of standard factored POMDP problems show that we can achieve an order of magnitude improvement in performance over previously proposed algorithms.