Satinder Singh

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Richard L. LewisProfessor of Psychology, Linguistics and Cognitive Science, University of MichiganDirección de correo verificada de umich.edu
Richard S. SuttonKeen, Amii, and University of AlbertaDirección de correo verificada de richsutton.com
Michael KearnsProfessor of Computer Science, University of PennsylvaniaDirección de correo verificada de cis.upenn.edu
Doina PrecupDeepMind and McGill UniversityDirección de correo verificada de cs.mcgill.ca
Andrew BartoUniversity of Massachusetts AmherstDirección de correo verificada de cs.umass.edu
Junhyuk OhResearch Scientist, DeepMindDirección de correo verificada de google.com
Yishay MansourTel Aviv UniversityDirección de correo verificada de tauex.tau.ac.il
Michael LittmanBrown UniversityDirección de correo verificada de brown.edu
Honglak LeeLG AI Research / U. MichiganDirección de correo verificada de umich.edu
David McAllesterProfessor, Toyota Technological Institute at ChicagoDirección de correo verificada de ttic.edu
Tommi JaakkolaMITDirección de correo verificada de csail.mit.edu
Michael WellmanProfessor of Computer Science & Engineering, University of MichiganDirección de correo verificada de umich.edu
David SilverDeepMind, UCLDirección de correo verificada de google.com
Hado van HasseltResearch Scientist, DeepMind; Honorary Professor, UCLDirección de correo verificada de google.com
Yevgeniy VorobeychikWashington University in Saint LouisDirección de correo verificada de wustl.edu
Edmund DurfeeProfessor Emeritus of Computer Science and Engineering, University of MichiganDirección de correo verificada de umich.edu
Peter StoneProfessor of Computer Science, The University of Texas at AustinDirección de correo verificada de cs.utexas.edu
Tom ZahavyStaff Research Scientist, Google DeepMindDirección de correo verificada de deepmind.com
Nan JiangAssistant Professor of Computer Science, UIUCDirección de correo verificada de illinois.edu
Xiaoxiao GuoLinkedInDirección de correo verificada de fb.com

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Satinder Singh

Google DeepMind / U. of Michigan

Dirección de correo verificada de umich.edu - Página principal

Reinforcement Learning Computational Game Theory Artificial Intelligence


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Policy Gradient Methods for Reinforcement Learning with Function Approximation R Sutton, D McAllester, S Singh, Y Mansour Neural Information Processing Systems, 1999	7558	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	4111	1999
Learning to act using real-time dynamic programming AG Barto, SJ Bradtke, SP Singh Artificial intelligence 72 (1-2), 81-138, 1995	1623	1995
Near-optimal reinforcement learning in polynomial time M Kearns, S Singh Machine learning 49, 209-232, 2002	1281	2002
Convergence of stochastic iterative dynamic programming algorithms T Jaakkola, M Jordan, S Singh Advances in neural information processing systems 6, 1993	1256	1993
Reinforcement learning with replacing eligibility traces SP Singh, RS Sutton Machine learning 22, 123-158, 1996	1013	1996
Action-conditional video prediction using deep networks in atari games J Oh, X Guo, H Lee, RL Lewis, S Singh Advances in neural information processing systems 28, 2015	990	2015
Intrinsically motivated reinforcement learning N Chentanez, A Barto, S Singh Advances in neural information processing systems 17, 2004	980	2004
Convergence results for single-step on-policy reinforcement-learning algorithms S Singh, T Jaakkola, ML Littman, C Szepesvári Machine learning 38, 287-308, 2000	950	2000
Eligibility traces for off-policy policy evaluation D Precup, R Sutton, S Singh Computer Science Department Faculty Publication Series, 80, 2000	869	2000
Graphical models for game theory M Kearns, ML Littman, S Singh arXiv preprint arXiv:1301.2281, 2013	799	2013
Predictive representations of state ML Littman, RS Sutton, S Singh Advances in neural information processing systems, 1555-1561, 2002	698	2002
Learning without state-estimation in partially observable Markovian decision processes SP Singh, T Jaakkola, MI Jordan Machine Learning Proceedings 1994, 284-292, 1994	602	1994
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	552	2004
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	528	2010
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	507	2002
Transfer of learning by composing solutions of elemental sequential tasks SP Singh Machine learning 8, 323-339, 1992	486	1992
Reinforcement Learning with Soft State Aggregation S Singh, T Jaakkola, M Jordan Neural Information Processing Systems, 1995	447	1995
Reward is enough D Silver, S Singh, D Precup, RS Sutton Artificial Intelligence 299, 103535, 2021	441	2021
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 27, 2014	433	2014

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