引用次数
引用: 150,478
H-指数: 90
I10-指数 : 352
出版物: 537
Theoretical Results on Reinforcement Learning with Temporally Abstract Options
Doina Precup , Richard S. Sutton , Satinder Singh
european conference on machine learning 382 -393
170
1998
Landmark learning: An illustration of associative search
Andrew G. Barto , Richard S. Sutton
Biological Cybernetics 42 ( 1) 1 -8
152
1981
Introduction: The Challenge of Reinforcement Learning
Richard S. Sutton
Machine Learning 8 ( 3) 225 -227
255
1992
Dyna, an integrated architecture for learning, planning, and reacting
Richard S. Sutton
Intelligence\/sigart Bulletin 2 ( 4) 160 -163
885
1991
Simulation of the classically conditioned nictitating membrane response by a neuron-like adaptive element: response topography, neuronal firing, and interstimulus intervals.
John W. Moore , John E. Desmond , Neil E. Berthier , Diana E.J. Blazis
Behavioural Brain Research 21 ( 2) 143 -154
83
1986
Learning to predict by the methods of temporal differences
Richard S. Sutton
Machine Learning 3 ( 1) 9 -44
7,173
1988
Neural Networks for Control
W. Thomas Miller , Richard S. Sutton , Paul J. Werbos
Smpte Journal
10
1995
Eligibility traces for off-policy policy evaluation
Doina Precup , Richard S. Sutton , Satinder Singh
Computer Science Department Faculty Publication Series 80 -80
933
2000
A unified framework for credit assignment
R.S. Sutton , G.E. Liepins
1990
Natural actorcritic algorithms.
M. Ghavamzadeh , S. Bhatnagar , M. Lee , R.S. Sutton
Automatica: A journal of IFAC the International Federation of Automatic Control 45 ( 11) 2471 -2482
711
2009
Application of connectionist learning methods to manufacturing process monitoring
J.A. Franklin , R.S. Sutton , C.W. Anderson
Proceedings IEEE International Symposium on Intelligent Control 1988 709 -712
10
1988
Learning a nonlinear model of a manufacturing process using multilayer connectionist networks
C.W. Anderson , J.A. Franklin , R.S. Sutton
international symposium on intelligent control 404 -409
9
1990
Advances in reinforcement learning and their implications for intelligent control
S.D. Whitehead , R.S. Sutton , D.H. Ballard
international symposium on intelligent control 1289 -1297
13
1990
Reinforcement Learning: An Introduction
R.S. Sutton , A.G. Barto
IEEE Transactions on Neural Networks 9 ( 5) 1054 -1054
46
1998
Learning and Sequential Decision Making
A. G. Barto , R. S. Sutton , C. J.C.H. Watkins
University of Massachusetts
621
1989
Sequential Decision Problems and Neural Networks
A. G. Barto , R. S. Sutton , C. J. C. H. Watkins
neural information processing systems 2 686 -693
48
1989
Two problems with backpropagation and other steepest-descent learning procedures for networks
R. S. Sutton
conference cognitive science
148
1986
Model-Free reinforcement learning with continuous action in practice
T. Degris , P. M. Pilarski , R. S. Sutton
advances in computing and communications 2177 -2182
254
2012
Timing and cue competition in conditioning of the nictitating membrane response of the rabbit (Oryctolagus cuniculus)
E. J. Kehoe , E. A. Ludvig , R. S. Sutton
Learning & Memory 20 ( 2) 97 -102
1
2013
Andrew Barto Satinder Singh Doina Precup Patrick M. Pilarski Charles Anderson Adam White Csaba Szepesvari Shalabh Bhatnagar A. Rupam Mahmood Thomas Degris Hamid Maei David Silver Martha White David McAllester Joseph Modayil Yishay Mansour Elliot A. Ludvig E James Kehoe Mohammad Ghavamzadeh Peter Stone