Satinder Singh

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Richard L. LewisProfessor of Psychology, Linguistics and Cognitive Science, University of MichiganEmail confirmado em umich.edu
Richard S. SuttonKeen, Amii, and University of AlbertaEmail confirmado em richsutton.com
Michael KearnsProfessor of Computer Science, University of PennsylvaniaEmail confirmado em cis.upenn.edu
Doina PrecupDeepMind and McGill UniversityEmail confirmado em cs.mcgill.ca
Andrew BartoUniversity of Massachusetts AmherstEmail confirmado em cs.umass.edu
Junhyuk OhResearch Scientist, DeepMindEmail confirmado em google.com
Yishay MansourTel Aviv UniversityEmail confirmado em tauex.tau.ac.il
Michael LittmanBrown UniversityEmail confirmado em brown.edu
David McAllesterProfessor, Toyota Technological Institute at ChicagoEmail confirmado em ttic.edu
Honglak LeeLG AI Research / U. MichiganEmail confirmado em umich.edu
Tommi JaakkolaMITEmail confirmado em csail.mit.edu
David SilverDeepMind, UCLEmail confirmado em google.com
Michael WellmanProfessor of Computer Science & Engineering, University of MichiganEmail confirmado em umich.edu
Hado van HasseltResearch Scientist, DeepMind; Honorary Professor, UCLEmail confirmado em google.com
Tom ZahavyStaff Research Scientist, Google DeepMindEmail confirmado em deepmind.com
Yevgeniy VorobeychikWashington University in Saint LouisEmail confirmado em wustl.edu
Edmund DurfeeProfessor Emeritus of Computer Science and Engineering, University of MichiganEmail confirmado em umich.edu
Nan JiangAssociate Professor of Computer Science, UIUCEmail confirmado em illinois.edu
Xiaoxiao GuoLinkedInEmail confirmado em fb.com
Marilyn WalkerProfessor of Computer Science and Engineering, University of California Santa CruzEmail confirmado em ucsc.edu

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Satinder Singh

Google DeepMind / U. of Michigan

Email confirmado em umich.edu - Página inicial

Reinforcement Learning Computational Game Theory Artificial Intelligence


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Policy Gradient Methods for Reinforcement Learning with Function Approximation R Sutton, D McAllester, S Singh, Y Mansour Neural Information Processing Systems, 1999	8726	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	4543	1999
Learning to act using real-time dynamic programming AG Barto, SJ Bradtke, SP Singh Artificial intelligence 72 (1-2), 81-138, 1995	1672	1995
Near-optimal reinforcement learning in polynomial time M Kearns, S Singh Machine learning 49, 209-232, 2002	1368	2002
Convergence of stochastic iterative dynamic programming algorithms T Jaakkola, M Jordan, S Singh Advances in neural information processing systems 6, 1993	1358	1993
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	1084	2015
Intrinsically motivated reinforcement learning N Chentanez, A Barto, S Singh Advances in neural information processing systems 17, 2004	1044	2004
Reinforcement learning with replacing eligibility traces SP Singh, RS Sutton Machine learning 22 (1), 123-158, 1996	1044	1996
Convergence results for single-step on-policy reinforcement-learning algorithms S Singh, T Jaakkola, ML Littman, C Szepesvári Machine learning 38, 287-308, 2000	1031	2000
Eligibility traces for off-policy policy evaluation D Precup, R Sutton, S Singh Computer Science Department Faculty Publication Series, 80, 2000	985	2000
Graphical models for game theory M Kearns, ML Littman, S Singh arXiv preprint arXiv:1301.2281, 2013	817	2013
Predictive representations of state ML Littman, RS Sutton, S Singh Advances in neural information processing systems, 1555-1561, 2002	727	2002
Learning without state-estimation in partially observable Markovian decision processes SP Singh, T Jaakkola, MI Jordan Machine Learning Proceedings 1994, 284-292, 1994	627	1994
Reward is enough D Silver, S Singh, D Precup, RS Sutton Artificial Intelligence 299, 103535, 2021	596	2021
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	582	2010
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	576	2004
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	519	2002
Transfer of learning by composing solutions of elemental sequential tasks SP Singh Machine learning 8, 323-339, 1992	502	1992
Reinforcement Learning with Soft State Aggregation S Singh, T Jaakkola, M Jordan Neural Information Processing Systems, 1995	475	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 27, 2014	460	2014

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