Reinforcement Learning and Artificial Intelligence (2003)

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by Richard S. Sutton

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13 A unifying framework for computational reinforcement learning theory – Lihong Li - 2009
1134 Reinforcement learning: a survey – Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore - 1996
Learning Methods for Sequential Decision Making with Imperfect Representations – Shivaram Kalyanakrishnan - 2011
1 A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control – Jong Min Lee - 2004
3 Hierarchical Reinforcement Learning: A Hybrid Approach – Malcolm Ross Kinsella Ryan - 2002
12 A Causal Approach to Hierarchical Decomposition in Reinforcement Learning – Anders Jonsson - 2006
5 Reinforcement learning for factored markov decision processes – Brian Sallans - 2002
4 Focus of attention in reinforcement learning – Lihong Li, Vadim Bulitko, Russell Greiner - 2004
342 Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning – Richard Sutton, Doina Precup, Satinder Singh - 1999
55 Temporal Abstraction in Reinforcement Learning – Doina Precup - 2000
51 Between MDPs and semi-MDPs: Learning, planning, and representing knowledge at multiple temporal scales – Richard S. Sutton, Doina Precup - 1998
1 Hung and Pham Hong Thai. On Checking Parallel Real-Time Systems for Linear Duration Invariants – David J. Finton - 2002
On Learning with Imperfect Representations – Shivaram Kalyanakrishnan, Peter Stone
30 Towards a Unified Theory of State Abstraction for MDPs – Lihong Li, Thomas J. Walsh, Michael L. Littman - 2006
85 Reinforcement learning for RoboCup-soccer keepaway – Peter Stone, Richard S. Sutton, Gregory Kuhlmann - 2005
158 Algorithms for Sequential Decision Making – Michael Lederman Littman - 1996
119 Recent advances in hierarchical reinforcement learning – Andrew G. Barto - 2003
Characterizing Reinforcement Learning Methods through Parameterized Learning Problems – Shivaram Kalyanakrishnan, Peter Stone - 2011
Synthesis Lectures on Artificial Intelligence and Machine Learning – Csaba Szepesvári - 2009