Technical update: Least-squares temporal difference learning (2002)

by Justin A. Boyan
Venue:Machine Learning
Citations:87 - 2 self

Active Bibliography

95 Least-Squares Temporal Difference Learning – Justin A. Boyan - 1999
1 A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control – Jong Min Lee - 2004
18 A unifying framework for computational reinforcement learning theory – Lihong Li - 2009
Synthesis Lectures on Artificial Intelligence and Machine Learning – Csaba Szepesvári - 2009
3 Reinforcement learning algorithms for MDPs – Csaba Szepesvári - 2009
63 Algorithms for Reinforcement Learning – Csaba Szepesvári - 2009
An Object-oriented Representation for Efficient Reinforcement Learning – Gregorio Diuk Wasser, Michael L. Littman, Carlos Gregorio, Diuk Wasser, Carlos Gregorio Diuk Wasser, Dissertation Director, Michael L. Littman - 2010
3 Learning Methods for Sequential Decision Making with Imperfect Representations – Shivaram Kalyanakrishnan - 2011
2 Learning Evaluation Functions – Justin A. Boyan, Scott E. Fahlman, Tom Mitchell - 1996
25 Incremental least-squares temporal difference learning – Alborz Geramifard, Michael Bowling, Richard S. Sutton - 2006
3 Hierarchical Reinforcement Learning: A Hybrid Approach – Malcolm Ross Kinsella Ryan - 2002
112 Reinforcement Learning In Continuous Time and Space – Kenji Doya - 2000
2 Evolutionary Computation versus Reinforcement Learning – Jürgen Schmidhuber - 2000
Multi-step Linear Dyna-style Planning – Hengshuai Yao, Shalabh Bhatnagar, Dongcui Diao
2 Reinforcement Learning and Artificial Intelligence – Richard S. Sutton - 2003
1298 Reinforcement learning: a survey – Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore - 1996
161 Recent advances in hierarchical reinforcement learning – Andrew G. Barto - 2003
On Learning with Imperfect Representations – Shivaram Kalyanakrishnan, Peter Stone
3 Title of the Book! – Name Of Author