ADAPTIVE STEP-SIZES FOR REINFORCEMENT LEARNING

作者: William C Dabney

DOI: 10.7275/.0

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参考文章(71)
Kevin Bache, Moshe Lichman, UCI Machine Learning Repository University of California, School of Information and Computer Science. ,(2007)
Richard S. Sutton, Gain Adaptation Beats Least Squares ,(2006)
Nicol N. Schraudolph, Online Learning with Adaptive Local Step Sizes Springer, London. pp. 151- 156 ,(1999) , 10.1007/978-1-4471-0877-1_13
Thomas G. Dietterich, The MAXQ Method for Hierarchical Reinforcement Learning international conference on machine learning. pp. 118- 126 ,(1998)
Richard Dearden, Nir Friedman, David Andre, Model based Bayesian exploration uncertainty in artificial intelligence. pp. 150- 159 ,(1999)
J. Andrew Bagnell, Jeff Schneider, Covariant policy search international joint conference on artificial intelligence. pp. 1019- 1024 ,(2003) , 10.1184/R1/6552458.V1
John N. Tsitsiklis, Dimitri P. Bertsekas, Neuro-dynamic programming ,(1996)
Malcolm J. A. Strens, A Bayesian Framework for Reinforcement Learning international conference on machine learning. pp. 943- 950 ,(2000)