SarsaLandmark: an algorithm for learning in POMDPs with landmarks
Michael R. James and Satinder Singh, 2009
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Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement
Michael T. Todd, Yael Niv, and Jonathan D. Cohen, 2009
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Analysis of an Evolutionary Reinforcement Learning Method in a Multiagent Domain
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner, 2008
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Looping suffix tree-based inference of partially observable hidden state
Michael P. Holmes and Charles Lee Isbell, Jr, 2006
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Anytime Point-Based Approximations for Large POMDPs
Joelle Pineau, Geoffrey J. Gordon, and Sebastian Thrun, 2006
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Scaling Internal-State Policy-Gradient Methods for POMDPs
Douglas Aberdeen and Jonathan Baxter, 2002
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An $epsilon$-Optimal Grid-Based Algorithm for Partially Observable Markov Decision Processes
Blai Bonet, 2002
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On the Existence of Fixed Points for Q-Learning and Sarsa in Partially Observable Domains
Theodore J. Perkins and Mark D. Pendrith, 2002
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Reinforcement Learning for POMDPs Based on Action Values and Stochastic Optimization
Theodore J. Perkins, 2002
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Evolutionary Search, Stochastic Policies with Memory, and Reinforcement Learning with Hidden State
Matthew R. Glickman and Katia Sycara, 2001
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Value-Function Approximations for Partially Observable Markov Decision Processes
Milos Hauskrecht, 2000
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Monte Carlo POMDPs
Sebastian Thrun, 2000
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Reinforcement Learning Using Approximate Belief States
Andrés Rodríguez, Ronald Parr, and Daphne Koller, 1999
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Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes
John Loch and Satinder Singh, 1998
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An Analysis of Direct Reinforcement Learning in Non-Markovian Domains
Mark D. Pendrith and Michael J. McGarity, 1998
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Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto, 1998
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Reinforcement Learning with Selective Perception and Hidden State
Andrew Kachites McCallum, 1996
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Reinforcement learning with replacing eligibility traces
Satinder P. Singh and Richard S. Sutton, 1996
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Reinforcement Learning Algorithm for Partially Observable Markov Problems
Tommi Jaakkola, Satinder P. Singh, and Michael I. Jordan, 1995
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Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State
R. Andrew McCallum, 1995
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Approximating Optimal Policies for Partially Observable Stochastic Domains
Ronald Parr and Stuart Russell, 1995
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Acting optimally in partially observable stochastic domains
Anthony R. Cassandra, Leslie Pack Kaelbling, and Michael L. Littman, 1994
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Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Satinder P. Singh, Tommi Jaakkola, and Michael I. Jordan, 1994
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Reinforcement learning with hidden states
Long-Ji Lin and Tom M. Mitchell, 1993
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Overcoming Incomplete Perception with Utile Distinction Memory
R. Andrew McCallum, 1993
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Reinforcement Learning with Perceptual Aliasing: The Perceptual Distinctions Approach
Lonnie Chrisman, 1992
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Cost-Sensitive Reinforcement Learning for Adaptive Classification and Control
Ming Tan, 1991
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Learning to perceive and act by trial and error
Steven D. Whitehead and Dana H. Ballard, 1991
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A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms
George E. Monahan, 1982
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The Optimal Control of Partially Observable Markov Processes Over the Infinite Horizon: Discounted Costs
Edward J. Sondik, 1978
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Optimal Control of Markov Processes with Incomplete State Information
K. J. Åström, 1965
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