Satinder Singh
Satinder Singh
Computer Science and Engineering, University of Michigan and DeepMind
Verified email at - Homepage
Cited by
Cited by
Policy Gradient Methods for Reinforcement Learning with Function Approximation
R Sutton, D McAllester, S Singh, Y Mansour
Neural Information Processing Systems, 1999
Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
RS Sutton, D Precup, S Singh
Artificial intelligence 112 (1-2), 181-211, 1999
Learning to act using real-time dynamic programming
AG Barto, SJ Bradtke, SP Singh
Artificial intelligence 72 (1-2), 81-138, 1995
Near-optimal reinforcement learning in polynomial time
M Kearns, S Singh
Machine learning 49 (2), 209-232, 2002
On the convergence of stochastic iterative dynamic programming algorithms
T Jaakkola, MI Jordan, SP Singh
Neural computation 6 (6), 1185-1201, 1994
Reinforcement learning with replacing eligibility traces
SP Singh, RS Sutton
Machine learning 22 (1), 123-158, 1996
Convergence results for single-step on-policy reinforcement-learning algorithms
S Singh, T Jaakkola, ML Littman, C Szepesvári
Machine learning 38 (3), 287-308, 2000
Intrinsically motivated reinforcement learning
N Chentanez, A Barto, S Singh
Advances in neural information processing systems 17, 2004
Action-conditional video prediction using deep networks in atari games
J Oh, X Guo, H Lee, R Lewis, S Singh
arXiv preprint arXiv:1507.08750, 2015
Graphical models for game theory
M Kearns, ML Littman, S Singh
arXiv preprint arXiv:1301.2281, 2013
Predictive representations of state
ML Littman, RS Sutton, S Singh
Advances in neural information processing systems, 1555-1561, 2002
Eligibility traces for off-policy policy evaluation
D Precup, R Sutton, S Singh
Computer Science Department Faculty Publication Series, 80, 2000
Learning without state-estimation in partially observable Markovian decision processes
SP Singh, T Jaakkola, MI Jordan
Machine Learning Proceedings 1994, 284-292, 1994
Reinforcement learning algorithm for partially observable Markov decision problems
T Jaakkola, SP Singh, MI Jordan
Advances in neural information processing systems, 345-352, 1995
Intrinsically motivated learning of hierarchical collections of skills
AG Barto, S Singh, N Chentanez
Proceedings of the 3rd International Conference on Development and Learning …, 2004
Transfer of learning by composing solutions of elemental sequential tasks
SP Singh
Machine learning 8 (3), 323-339, 1992
Optimizing dialogue management with reinforcement learning: Experiments with the NJFun system
S Singh, D Litman, M Kearns, M Walker
Journal of Artificial Intelligence Research 16, 105-133, 2002
Intrinsically motivated reinforcement learning: An evolutionary perspective
S Singh, RL Lewis, AG Barto, J Sorg
IEEE Transactions on Autonomous Mental Development 2 (2), 70-82, 2010
Reinforcement Learning with Soft State Aggregation
S Singh, T Jaakkola, M Jordan
Neural Information Processing Systems, 1995
Deep learning for real-time Atari game play using offline Monte-Carlo tree search planning
X Guo, S Singh, H Lee, RL Lewis, X Wang
Advances in neural information processing systems, 3338-3346, 2014
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