Exploiting Best-Match Equations for Efficient Reinforcement Learning
Harm van Seijen, Shimon Whiteson, Hado van Hasselt, and Marco Wiering, 2011
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Insights in Reinforcement Learning: formal analysis and empirical evaluation of temporal-difference learning algorithms
Hado Philip van Hasselt, 2011
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Relative Entropy Policy Search
Jan Peters, Katharina Mülling, and Yasemin Altün, 2010
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Model-based reinforcement learning with nearly tight exploration complexity bounds
István Szita and Csaba Szepesvári, 2010
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Reinforcement learning of motor skills in high dimensions: A path integral approach
Evangelos Theodorou, Jonas Buchli, and Stefan Schaal, 2010
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The CMA Evolution Strategy: A Tutorial
Nikolaus Hansen, 2009
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Learning motor primitives for robotics
Jens Kober and Jan Peters, 2009
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Efficient covariance matrix update for variable metric evolution strategies
Thorsten Suttorp, Nikolaus Hansen, and Christian Igel, 2009
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A Theoretical and Empirical Analysis of Expected Sarsa
Harm van Seijen, Hado van Hasselt, Shimon Whiteson, and Marco Wiering, 2009
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Incremental Natural Actor-Critic Algorithms
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Ghavamzadeh, and Mark Lee, 2008
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Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Faustino Gomez, Jürgen Schmidhuber, and Risto Miikkulainen, 2008
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Similarities and differences between policy gradient methods and evolution strategies
Verena Heidrich-Meisner and Christian Igel, 2008
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Evolution Strategies for Direct Policy Search
Verena Heidrich-Meisner and Christian Igel, 2008
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Genetic Programming: An Introduction and Tutorial, with a Survey of Techniques and Applications
William B. Langdon, Riccardo Poli, Nicholas Freitag McPhee, and John R. Koza, 2008
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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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Reinforcement learning of motor skills with policy gradients
Jan Peters and Stefan Schaal, 2008
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Natural Actor-Critic
Jan Peters and Stefan Schaal, 2008
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Sample-based Learning and Search with Permanent and Transient Memories
David Silver, Richard S. Sutton, and Martin Müller, 2008
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Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
Richard S. Sutton, Csaba Szepesvári, Alborz Geramifard, and Michael Bowling, 2008
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Sample Complexity of Policy Search with Known Dynamics
Peter L. Bartlett and Ambuj Tewari, 2007
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Bayesian actor-critic algorithms
Mohammad Ghavamzadeh and Yaakov Engel, 2007
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Bayesian Policy Gradient Algorithms
Mohammad Ghavamzadeh and Yaakov Engel, 2007
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Batch Reinforcement Learning in a Complex Domain
Shivaram Kalyanakrishnan and Peter Stone, 2007
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Large Scale Reinforcement Learning using Q-Sarsa($łambda$) and Cascading Neural Networks
Steffen Nissen, 2007
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Representation Transfer for Reinforcement Learning
Matthew E. Taylor and Peter Stone, 2007
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Adaptive Representations for Reinforcement Learning
Shimon Azariah Whiteson, 2007
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Evolutionary Function Approximation for Reinforcement Learning
Shimon Whiteson and Peter Stone, 2006
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On-line evolutionary computation for reinforcement learning in stochastic domains
Shimon Whiteson and Peter Stone, 2006
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Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method
Martin Riedmiller, 2005
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A Tutorial on the Cross-Entropy Method
Pieter-Tjerk de Boer, Dirk P. Kroese, Shie Mannor, and Reuven Y. Rubinstein, 2005
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Machine Learning for Fast Quadrupedal Locomotion
Nate Kohl and Peter Stone, 2004
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Efficient Evolution of Neural Networks Through Complexification
Kenneth Owen Stanley, 2004
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On Actor-Critic Algorithms
Vijay R. Konda and John N. Tsitsiklis, 2003
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Reinforcement Learning as Classification: Leveraging Modern Classifiers
Michail G. Lagoudakis and Ronald Parr, 2003
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Scaling Internal-State Policy-Gradient Methods for POMDPs
Douglas Aberdeen and Jonathan Baxter, 2002
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Approximately Optimal Approximate Reinforcement Learning
Sham Kakade and John Langford, 2002
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Learning from Scarce Experience
Leonid Peshkin and Christian R. Shelton, 2002
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Infinite-Horizon Policy-Gradient Estimation
Jonathan Baxter and Peter L. Bartlett, 2001
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A Natural Policy Gradient
Sham Kakade, 2001
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Reinforcement Learning in POMDP's via Direct Gradient Ascent
Jonathan Baxter and Peter L. Bartlett, 2000
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Policy Search via Density Estimation
Andrew Y. Ng, Ronald Parr, and Daphne Koller, 2000
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PEGASUS: A policy search method for large MDPs and POMDPs
Andrew Y. Ng and Michael Jordan, 2000
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Policy Gradient Methods for Reinforcement Learning with Function Approximation
Richard S. Sutton, David A. McAllester, Satinder P. Singh, and Yishay Mansour, 2000
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Gradient Descent for General Reinforcement Learning
Leemon Baird and Andrew Moore, 1999
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Solving Non-Markovian Control Tasks with Neuro-Evolution
Faustino J. Gomez and Risto Miikkulainen, 1999
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Evolutionary Algorithms for Reinforcement Learning
David E. Moriarty, Alan C. Schultz, and John J. Grefenstette, 1999
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Robot Shaping: An Experiment in Behavior Engineering
Marco Dorigo and Marco Colombetti, 1998
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Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto, 1998
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Neuro-Dynamic Programming
Dimitri P. Bertsekas and John N. Tsitsiklis, 1996
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Reinforcement learning with replacing eligibility traces
Satinder P. Singh and Richard S. Sutton, 1996
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On-line Q-learning using connectionist systems
G. A. Rummery and M. Niranjan, 1994
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Prioritized Sweeping: Reinforcement Learning with Less Data and Less Time
Andrew W. Moore and Christopher G. Atkeson, 1993
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Efficient learning and planning within the Dyna framework
Jing Peng and Ronald J. Williams, 1993
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Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching
Long-Ji Lin, 1992
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Q-Learning
Christopher J. C. H. Watkins and Peter Dayan, 1992
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Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
Ronald J. Williams, 1992
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Learning Sequential Decision Rules Using Simulation Models and Competition
John J. Grefenstette, Connie Loggia Ramsey, and Alan C. Schultz, 1990
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Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming
Richard S. Sutton, 1990
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Neuronlike adaptive elements that can solve difficult learning control problems
Andrew G. Barto, Richard S. Sutton, and Charles W. Anderson, 1983
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