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Satinder P. Singh: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Charles Lee Isbell Jr., Michael J. Kearns, David P. Kormann, Satinder P. Singh, Peter Stone
    Cobot in LambdaMOO: A Social Statistics Agent. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:36-41 [Conf]
  2. Michael R. James, Satinder P. Singh
    Planning in Models that Combine Memory with Predictive Representations of State. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:987-992 [Conf]
  3. Michael J. Kearns, Charles Lee Isbell Jr., Satinder P. Singh, Diane J. Litman, Jessica Howe
    CobotDS: A Spoken Dialogue System for Chat. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2002, pp:425-430 [Conf]
  4. Satinder P. Singh
    Reinforcement Learning with a Hierarchy of Abstract Models. [Citation Graph (0, 0)][DBLP]
    AAAI, 1992, pp:202-207 [Conf]
  5. Satinder P. Singh
    Reinforcement Learning Algorithms for Average-Payoff Markovian Decision Processes. [Citation Graph (0, 0)][DBLP]
    AAAI, 1994, pp:700-705 [Conf]
  6. Satinder P. Singh, Michael J. Kearns, Diane J. Litman, Marilyn A. Walker
    Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:645-651 [Conf]
  7. Vishal Soni, Satinder P. Singh
    Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  8. David Wingate, Satinder P. Singh
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  9. Charles Lee Isbell Jr., Christian R. Shelton, Michael J. Kearns, Satinder P. Singh, Peter Stone
    A social reinforcement learning agent. [Citation Graph (0, 0)][DBLP]
    Agents, 2001, pp:377-384 [Conf]
  10. Peter Stone, Michael L. Littman, Satinder P. Singh, Michael J. Kearns
    ATTac-2000: an adaptive autonomous bidding agent. [Citation Graph (0, 0)][DBLP]
    Agents, 2001, pp:238-245 [Conf]
  11. Christopher Kiekintveld, Michael P. Wellman, Satinder P. Singh, Joshua Estelle, Yevgeniy Vorobeychik, Vishal Soni, Matthew R. Rudary
    Distributed Feedback Control for Decision Making on Supply Chains. [Citation Graph (0, 0)][DBLP]
    ICAPS, 2004, pp:384-392 [Conf]
  12. Joshua Estelle, Yevgeniy Vorobeychik, Michael P. Wellman, Satinder P. Singh, Christopher Kiekintveld, Vishal Soni
    Strategic Interactions in the TAC 2003 Supply Chain Tournament. [Citation Graph (0, 0)][DBLP]
    Computers and Games, 2004, pp:316-331 [Conf]
  13. Diane J. Litman, Michael S. Kearns, Satinder P. Singh, Marilyn A. Walker
    Automatic Optimization of Dialogue Management. [Citation Graph (0, 0)][DBLP]
    COLING, 2000, pp:502-508 [Conf]
  14. Michael J. Kearns, Satinder P. Singh
    Bias-Variance Error Bounds for Temporal Difference Updates. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:142-147 [Conf]
  15. Lawrence K. Saul, Satinder P. Singh
    Markov Decision Processes in Large State Spaces. [Citation Graph (0, 0)][DBLP]
    COLT, 1995, pp:281-288 [Conf]
  16. Lawrence K. Saul, Satinder P. Singh
    Learning Curve Bounds for a Markov Decision Process with Undiscounted Rewards. [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:147-156 [Conf]
  17. Doina Precup, Richard S. Sutton, Satinder P. Singh
    Theoretical Results on Reinforcement Learning with Temporally Abstract Options. [Citation Graph (0, 0)][DBLP]
    ECML, 1998, pp:382-393 [Conf]
  18. Michael R. James, Satinder P. Singh
    Learning and discovery of predictive state representations in dynamical systems with reset. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  19. Michael J. Kearns, Satinder P. Singh
    Near-Optimal Reinforcement Learning in Polynominal Time. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:260-268 [Conf]
  20. John Loch, Satinder P. Singh
    Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:323-331 [Conf]
  21. Kary Myers, Michael J. Kearns, Satinder P. Singh, Marilyn A. Walker
    A Boosting Approach to Topic Spotting on Subdialogues. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:655-662 [Conf]
  22. Doina Precup, Richard S. Sutton, Satinder P. Singh
    Eligibility Traces for Off-Policy Policy Evaluation. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:759-766 [Conf]
  23. Matthew R. Rudary, Satinder P. Singh
    Predictive linear-Gaussian models of controlled stochastic dynamical systems. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:777-784 [Conf]
  24. Matthew R. Rudary, Satinder P. Singh, Martha E. Pollack
    Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  25. Satinder P. Singh
    Transfer of Learning Across Compositions of Sequentail Tasks. [Citation Graph (0, 0)][DBLP]
    ML, 1991, pp:348-352 [Conf]
  26. Satinder P. Singh
    Scaling Reinforcement Learning Algorithms by Learning Variable Temporal Resolution Models. [Citation Graph (0, 0)][DBLP]
    ML, 1992, pp:406-415 [Conf]
  27. Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan
    Learning Without State-Estimation in Partially Observable Markovian Decision Processes. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:284-292 [Conf]
  28. Satinder P. Singh, Michael L. Littman, Nicholas K. Jong, David Pardoe, Peter Stone
    Learning Predictive State Representations. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:712-719 [Conf]
  29. Richard S. Sutton, Doina Precup, Satinder P. Singh
    Intra-Option Learning about Temporally Abstract Actions. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:556-564 [Conf]
  30. David Wingate, Satinder P. Singh
    Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1017-1024 [Conf]
  31. Britton Wolfe, Michael R. James, Satinder P. Singh
    Learning predictive state representations in dynamical systems without reset. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:980-987 [Conf]
  32. Britton Wolfe, Satinder P. Singh
    Predictive state representations with options. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1025-1032 [Conf]
  33. Michael R. James, Britton Wolfe, Satinder P. Singh
    Combining Memory and Landmarks with Predictive State Representations. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:734-739 [Conf]
  34. Yevgeniy Vorobeychik, Michael P. Wellman, Satinder P. Singh
    Learning Payoff Functions in Infinite Games. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:977-982 [Conf]
  35. David Wingate, Vishal Soni, Britton Wolfe, Satinder P. Singh
    Relational Knowledge with Predictive State Representations. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:2035-2040 [Conf]
  36. N. E. Berthier, Satinder P. Singh, Andrew G. Barto, James C. Houk
    A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:611-618 [Conf]
  37. Timothy X. Brown, Hui Tong, Satinder P. Singh
    Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:982-988 [Conf]
  38. David A. Cohn, Satinder P. Singh
    Predicting Lifetimes in Dynamically Allocated Memory. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:939-945 [Conf]
  39. Peter Dayan, Satinder P. Singh
    Improving Policies without Measuring Merits. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:1059-1065 [Conf]
  40. Charles Lee Isbell Jr., Christian R. Shelton, Michael J. Kearns, Satinder P. Singh, Peter Stone
    Cobot: A Social Reinforcement Learning Agent. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1393-1400 [Conf]
  41. Tommi Jaakkola, Michael I. Jordan, Satinder P. Singh
    Convergence of Stochastic Iterative Dynamic Programming Algorithms. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:703-710 [Conf]
  42. Tommi Jaakkola, Satinder P. Singh, Michael I. Jordan
    Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:345-352 [Conf]
  43. Michael J. Kearns, Satinder P. Singh
    Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:996-1002 [Conf]
  44. Michael L. Littman, Michael J. Kearns, Satinder P. Singh
    An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:817-823 [Conf]
  45. Michael L. Littman, Richard S. Sutton, Satinder P. Singh
    Predictive Representations of State. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1555-1561 [Conf]
  46. David C. Parkes, Satinder P. Singh
    An MDP-Based Approach to Online Mechanism Design. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  47. David C. Parkes, Satinder P. Singh, Dimah Yanovsky
    Approximately Efficient Online Mechanism Design. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  48. Doina Precup, Richard S. Sutton, Cosmin Paduraru, Anna Koop, Satinder P. Singh
    Off-policy Learning with Options and Recognizers. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  49. Matthew R. Rudary, Satinder P. Singh
    A Nonlinear Predictive State Representation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  50. Satinder P. Singh
    The Efficient Learning of Multiple Task Sequences. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:251-258 [Conf]
  51. Satinder P. Singh, Dimitri P. Bertsekas
    Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:974-980 [Conf]
  52. Satinder P. Singh, Andrew G. Barto, Nuttapong Chentanez
    Intrinsically Motivated Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  53. Satinder P. Singh, Andrew G. Barto, Roderic A. Grupen, Christopher I. Connolly
    Robust Reinforcement Learning in Motion Planning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:655-662 [Conf]
  54. Satinder P. Singh, David Cohn
    How to Dynamically Merge Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  55. Satinder P. Singh, Peter Dayan
    Analytical Mean Squared Error Curves in Temporal Difference Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:1054-1060 [Conf]
  56. Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan
    Reinforcement Learning with Soft State Aggregation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:361-368 [Conf]
  57. Satinder P. Singh, Michael J. Kearns, Diane J. Litman, Marilyn A. Walker
    Reinforcement Learning for Spoken Dialogue Systems. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:956-962 [Conf]
  58. Richard S. Sutton, David A. McAllester, Satinder P. Singh, Yishay Mansour
    Policy Gradient Methods for Reinforcement Learning with Function Approximation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:1057-1063 [Conf]
  59. Richard S. Sutton, Satinder P. Singh, Doina Precup, Balaraman Ravindran
    Improved Switching among Temporally Abstract Actions. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:1066-1072 [Conf]
  60. John K. Williams, Satinder P. Singh
    Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:1073-1080 [Conf]
  61. Peter Stone, Richard S. Sutton, Satinder P. Singh
    Reinforcement Learning for 3 vs. 2 Keepaway [Citation Graph (0, 0)][DBLP]
    RoboCup, 2000, pp:249-258 [Conf]
  62. Satinder P. Singh, Vishal Soni, Michael P. Wellman
    Computing approximate bayes-nash equilibria in tree-games of incomplete information. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2004, pp:81-90 [Conf]
  63. Michael J. Kearns, Michael L. Littman, Satinder P. Singh
    Graphical Models for Game Theory. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:253-260 [Conf]
  64. Michael J. Kearns, Yishay Mansour, Satinder P. Singh
    Fast Planning in Stochastic Games. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:309-316 [Conf]
  65. Yishay Mansour, Satinder P. Singh
    On the Complexity of Policy Iteration. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:401-408 [Conf]
  66. David A. McAllester, Satinder P. Singh
    Approximate Planning for Factored POMDPs using Belief State Simplification. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:409-416 [Conf]
  67. Satinder P. Singh, Michael J. Kearns, Yishay Mansour
    Nash Convergence of Gradient Dynamics in General-Sum Games. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:541-548 [Conf]
  68. János A. Csirik, Michael L. Littman, Satinder P. Singh, Peter Stone
    FAucS : An FCC Spectrum Auction Simulator for Autonomous Bidding Agents. [Citation Graph (0, 0)][DBLP]
    WELCOM, 2001, pp:139-151 [Conf]
  69. Charles Lee Isbell Jr., Michael J. Kearns, Satinder P. Singh, Christian R. Shelton, Peter Stone, David P. Kormann
    Cobot in LambdaMOO: An Adaptive Social Statistics Agent. [Citation Graph (0, 0)][DBLP]
    Autonomous Agents and Multi-Agent Systems, 2006, v:13, n:3, pp:327-354 [Journal]
  70. Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh
    Learning to Act Using Real-Time Dynamic Programming. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1995, v:72, n:1-2, pp:81-138 [Journal]
  71. Richard S. Sutton, Doina Precup, Satinder P. Singh
    Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1999, v:112, n:1-2, pp:181-211 [Journal]
  72. Nicholas L. Cassimatis, Sean Luke, Simon D. Levy, Ross Gayler, Pentti Kanerva, Chris Eliasmith, Timothy W. Bickmore, Alan C. Schultz, Randall Davis, James A. Landay, Robert C. Miller, Eric Saund, Thomas F. Stahovich, Michael L. Littman, Satinder P. Singh, Shlomo Argamon, Shlomo Dubnov
    Reports on the 2004 AAAI Fall Symposia. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2005, v:26, n:1, pp:98-102 [Journal]
  73. Satinder P. Singh, Diane J. Litman, Michael J. Kearns, Marilyn A. Walker
    Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2002, v:16, n:, pp:105-133 [Journal]
  74. Peter Stone, Michael L. Littman, Satinder P. Singh, Michael J. Kearns
    ATTac-2000: An Adaptive Autonomous Bidding Agent. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2001, v:15, n:, pp:189-206 [Journal]
  75. Michael J. Kearns, Satinder P. Singh
    Near-Optimal Reinforcement Learning in Polynomial Time. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:49, n:2-3, pp:209-232 [Journal]
  76. Satinder P. Singh
    Introduction. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:49, n:2-3, pp:107-109 [Journal]
  77. Satinder P. Singh
    Transfer of Learning by Composing Solutions of Elemental Sequential Tasks. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1992, v:8, n:, pp:323-339 [Journal]
  78. Satinder P. Singh, Peter Dayan
    Analytical Mean Squared Error Curves for Temporal Difference Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:32, n:1, pp:5-40 [Journal]
  79. Satinder P. Singh, Tommi Jaakkola, Michael L. Littman, Csaba Szepesvári
    Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2000, v:38, n:3, pp:287-308 [Journal]
  80. Satinder P. Singh, Richard S. Sutton
    Reinforcement Learning with Replacing Eligibility Traces. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:22, n:1-3, pp:123-158 [Journal]
  81. Satinder P. Singh, Richard C. Yee
    An Upper Bound on the Loss from Approximate Optimal-Value Functions. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1994, v:16, n:3, pp:227-233 [Journal]
  82. Vishal Soni, Satinder P. Singh
    Abstraction in Predictive State Representations. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:639-644 [Conf]
  83. Satinder P. Singh, Michael R. James, Matthew R. Rudary
    Predictive State Representations: A New Theory for Modeling Dynamical Systems. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:512-518 [Conf]
  84. Matthew R. Rudary, Satinder P. Singh, David Wingate
    Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:501-508 [Conf]
  85. Ruggiero Cavallo, David C. Parkes, Satinder P. Singh
    Optimal Coordinated Planning Amongst Self-Interested Agents with Private State. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  86. Yevgeniy Vorobeychik, Michael P. Wellman, Satinder P. Singh
    Learning payoff functions in infinite games. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2007, v:67, n:1-2, pp:145-168 [Journal]

  87. Constraint satisfaction algorithms for graphical games. [Citation Graph (, )][DBLP]


  88. On discovery and learning of models with predictive representations of state for agents with continuous actions and observations. [Citation Graph (, )][DBLP]


  89. Approximate predictive state representations. [Citation Graph (, )][DBLP]


  90. SarsaLandmark: an algorithm for learning in POMDPs with landmarks. [Citation Graph (, )][DBLP]


  91. Transfer via soft homomorphisms. [Citation Graph (, )][DBLP]


  92. Linear options. [Citation Graph (, )][DBLP]


  93. History-dependent graphical multiagent models. [Citation Graph (, )][DBLP]


  94. Efficiently learning linear-linear exponential family predictive representations of state. [Citation Graph (, )][DBLP]


  95. Internal Rewards Mitigate Agent Boundedness. [Citation Graph (, )][DBLP]


  96. Planning with predictive state representations. [Citation Graph (, )][DBLP]


  97. Learning Graphical Game Models. [Citation Graph (, )][DBLP]


  98. Knowledge Combination in Graphical Multiagent Models. [Citation Graph (, )][DBLP]


  99. Strategic Interactions in a Supply Chain Game. [Citation Graph (, )][DBLP]


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