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Region-Based Dynamic Programming for Partially Observable Markov Decision Processes
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Exploiting Structure to Efficiently Solve Large Scale Partially Observable Markov Decision Processes
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Approximate Value-Directed Belief State Monitoring for Partially Observable Markov Decision Processes
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Model-Based Bayesian Reinforcement Learning in Complex Domains
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An Improved Policy Iteration Algorithm for Partially Observable MDPs
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Finding Approximate POMDP Solutions Through Belief Compression
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A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains
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Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes
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629
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Complexity of Finite-Horizon Markov Decision Process Problems
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Nonapproximability Results for Partially Observable Markov Decision Processes
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