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Michael L. Littman: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Dennis E. Egan, Michael Lesk, R. Daniel Ketchum, Carol C. Lochbaum, Joel R. Remde, Michael L. Littman, Thomas K. Landauer
    Hypertext for the Electronic Library? CORE Sample Results. [Citation Graph (1, 0)][DBLP]
    Hypertext, 1991, pp:299-312 [Conf]
  2. Lihong Li, Michael L. Littman
    Lazy Approximation for Solving Continuous Finite-Horizon MDPs. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:1175-1180 [Conf]
  3. Anthony R. Cassandra, Leslie Pack Kaelbling, Michael L. Littman
    Acting Optimally in Partially Observable Stochastic Domains. [Citation Graph (0, 0)][DBLP]
    AAAI, 1994, pp:1023-1028 [Conf]
  4. Michael S. Fulkerson, Michael L. Littman, Greg A. Keim
    Speeding Safely: Multi-Criteria Optimization in Probabilistic Planning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1997, pp:831- [Conf]
  5. Greg A. Keim, Noam M. Shazeer, Michael L. Littman, Sushant Agarwal, Catherine M. Cheves, Joseph Fitzgerald, Jason Grosland, Fan Jiang, Shannon Pollard, Karl Weinmeister
    PROVERB: The Probabilistic Cruciverbalist. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:710-717 [Conf]
  6. Michail G. Lagoudakis, Michael L. Littman
    Reinforcement Learning for Algorithm Selection. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:1081- [Conf]
  7. Michael L. Littman
    Probabilistic Propositional Planning: Representations and Complexity. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1997, pp:748-754 [Conf]
  8. Michael L. Littman
    Initial Experiments in Stochastic Satisfiability. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:667-672 [Conf]
  9. Michael L. Littman, Greg A. Keim, Noam M. Shazeer
    Solving Crosswords with PROVERB. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:914-915 [Conf]
  10. Michael L. Littman, Nishkam Ravi, Eitan Fenson, Rich Howard
    An Instance-Based State Representation for Network Repair. [Citation Graph (0, 0)][DBLP]
    AAAI, 2004, pp:287-292 [Conf]
  11. Stephen M. Majercik, Michael L. Littman
    Using Caching to Solve Larger Probabilistic Planning Problems. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1998, pp:954-959 [Conf]
  12. Stephen M. Majercik, Michael L. Littman
    Contingent Planning Under Uncertainty via Stochastic Satisfiability. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:549-556 [Conf]
  13. Nishkam Ravi, Nikhil Dandekar, Preetham Mysore, Michael L. Littman
    Activity Recognition from Accelerometer Data. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:1541-1546 [Conf]
  14. David L. Roberts, Mark J. Nelson, Charles Lee Isbell Jr., Michael Mateas, Michael L. Littman
    Targeting Specific Distributions of Trajectories in MDPs. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  15. Noam M. Shazeer, Michael L. Littman, Greg A. Keim
    Solving Crossword Puzzles as Probabilistic Constraint Satisfaction. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:156-162 [Conf]
  16. Jiefu Shi, Michael L. Littman
    Towards Approximately Optimal Poker. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:1094- [Conf]
  17. 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]
  18. Stephen M. Majercik, Michael L. Littman
    MAXPLAN: A New Approach to Probabilistic Planning. [Citation Graph (0, 0)][DBLP]
    AIPS, 1998, pp:86-93 [Conf]
  19. Paul S. A. Reitsma, Peter Stone, János A. Csirik, Michael L. Littman
    Self-Enforcing Strategic Demand Reduction. [Citation Graph (0, 0)][DBLP]
    AMEC, 2002, pp:289-306 [Conf]
  20. Peter Stone, Robert E. Schapire, János A. Csirik, Michael L. Littman, David A. McAllester
    ATTac-2001: A Learning, Autonomous Bidding Agent. [Citation Graph (0, 0)][DBLP]
    AMEC, 2002, pp:143-160 [Conf]
  21. Carlos Diuk, Alexander L. Strehl, Michael L. Littman
    A hierarchical approach to efficient reinforcement learning in deterministic domains. [Citation Graph (0, 0)][DBLP]
    AAMAS, 2006, pp:313-319 [Conf]
  22. Michael L. Littman, Peter Stone
    Implicit Negotiation in Repeated Games. [Citation Graph (0, 0)][DBLP]
    ATAL, 2001, pp:393-404 [Conf]
  23. Paul S. A. Reitsma, Peter Stone, János Csirik, Michael L. Littman
    Randomized strategic demand reduction: getting more by asking for less. [Citation Graph (0, 0)][DBLP]
    AAMAS, 2002, pp:162-163 [Conf]
  24. Michael L. Littman
    Review: Computer Language Games. [Citation Graph (0, 0)][DBLP]
    Computers and Games, 2000, pp:396-404 [Conf]
  25. Jiefu Shi, Michael L. Littman
    Abstraction Methods for Game Theoretic Poker. [Citation Graph (0, 0)][DBLP]
    Computers and Games, 2000, pp:333-345 [Conf]
  26. Michael L. Littman
    Tutorial: Learning Topics in Game-Theoretic Decision Making. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:1- [Conf]
  27. Laurence Brothers, James D. Hollan, Jakob Neilsen, Scott Stornetta, Steven P. Abney, George W. Furnas, Michael L. Littman
    Supporting Informal Communication via Ephemeral Interest Groups. [Citation Graph (0, 0)][DBLP]
    CSCW, 1992, pp:84-90 [Conf]
  28. Robert B. Allen, Pascal Obry, Michael L. Littman
    An interface for navigating clustered document sets returned by queries. [Citation Graph (0, 0)][DBLP]
    COOCS, 1993, pp:166-171 [Conf]
  29. Michael L. Littman, Nishkam Ravi, Eitan Fenson, Rich Howard
    Reinforcement Learning for Autonomic Network Repair. [Citation Graph (0, 0)][DBLP]
    ICAC, 2004, pp:284-285 [Conf]
  30. Michael L. Littman, David H. Ackley
    Adaptation in Constant Utility Non-Stationary Environments. [Citation Graph (0, 0)][DBLP]
    ICGA, 1991, pp:136-142 [Conf]
  31. Fan Jiang, Michael L. Littman
    Approximate Dimension Equalization in Vector-based Information Retrieval. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:423-430 [Conf]
  32. Michail G. Lagoudakis, Michael L. Littman
    Algorithm Selection using Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:511-518 [Conf]
  33. Michael L. Littman
    Friend-or-Foe Q-learning in General-Sum Games. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:322-328 [Conf]
  34. Michael L. Littman
    Markov Games as a Framework for Multi-Agent Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:157-163 [Conf]
  35. Michael L. Littman, Anthony R. Cassandra, Leslie Pack Kaelbling
    Learning Policies for Partially Observable Environments: Scaling Up. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:362-370 [Conf]
  36. Michael L. Littman, Fan Jiang, Greg A. Keim
    Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:314-322 [Conf]
  37. Michael L. Littman, Csaba Szepesvári
    A Generalized Reinforcement-Learning Model: Convergence and Applications. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:310-318 [Conf]
  38. Robert E. Schapire, Peter Stone, David A. McAllester, Michael L. Littman, János A. Csirik
    Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:546-553 [Conf]
  39. 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]
  40. Alexander L. Strehl, Michael L. Littman
    A theoretical analysis of Model-Based Interval Estimation. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:856-863 [Conf]
  41. Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman
    PAC model-free reinforcement learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:881-888 [Conf]
  42. Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh
    Experience-efficient learning in associative bandit problems. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:889-896 [Conf]
  43. Alexander L. Strehl, Michael L. Littman
    An Empirical Evaluation of Interval Estimation for Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2004, pp:128-135 [Conf]
  44. Leslie Pack Kaelbling, Michael L. Littman, Anthony R. Cassandra
    Partially Observable Markov Decision Processes for Artificial Intelligence. [Citation Graph (0, 0)][DBLP]
    KI, 1995, pp:1-17 [Conf]
  45. David H. Ackley, Michael L. Littman
    Generalization and Scaling in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1989, pp:550-557 [Conf]
  46. Justin A. Boyan, Michael L. Littman
    Exact Solutions to Time-Dependent MDPs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:1026-1032 [Conf]
  47. Justin A. Boyan, Michael L. Littman
    Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:671-678 [Conf]
  48. Sanjoy Dasgupta, Michael L. Littman, David A. McAllester
    PAC Generalization Bounds for Co-training. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:375-382 [Conf]
  49. 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]
  50. Michael L. Littman, Richard S. Sutton, Satinder P. Singh
    Predictive Representations of State. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1555-1561 [Conf]
  51. Martin Zinkevich, Amy R. Greenwald, Michael L. Littman
    Cyclic Equilibria in Markov Games. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  52. Peter D. Turney, Michael L. Littman, Jeffrey Bigham, Victor Shnayder
    Combining independent modules in lexical multiple-choice problems. [Citation Graph (0, 0)][DBLP]
    RANLP, 2003, pp:101-110 [Conf]
  53. Leslie Pack Kaelbling, Michael L. Littman, Anthony R. Cassandra
    Partially Observable Markov Decision Processes for Artificial Intelligence. [Citation Graph (0, 0)][DBLP]
    Reasoning with Uncertainty in Robotics, 1995, pp:146-163 [Conf]
  54. Michail G. Lagoudakis, Ronald Parr, Michael L. Littman
    Least-Squares Methods in Reinforcement Learning for Control. [Citation Graph (0, 0)][DBLP]
    SETN, 2002, pp:249-260 [Conf]
  55. Michael L. Littman, Peter Stone
    A polynomial-time nash equilibrium algorithm for repeated games. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2003, pp:48-54 [Conf]
  56. Bob Rehder, Michael L. Littman, Susan T. Dumais, Thomas K. Landauer
    Automatic 3-Language Cross-Language Information Retrieval with Latent Semantic Indexing. [Citation Graph (0, 0)][DBLP]
    TREC, 1997, pp:233-239 [Conf]
  57. Anthony R. Cassandra, Michael L. Littman, Nevin Lianwen Zhang
    Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:54-61 [Conf]
  58. Judy Goldsmith, Michael L. Littman, Martin Mundhenk
    The Complexity of Plan Existence and Evaluation in Probabilistic Domains. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:182-189 [Conf]
  59. 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]
  60. Michael L. Littman, Thomas Dean, Leslie Pack Kaelbling
    On the Complexity of Solving Markov Decision Problems. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:394-402 [Conf]
  61. 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]
  62. Bethany R. Leffler, Michael L. Littman, Alexander L. Strehl, Thomas J. Walsh
    Efficient Exploration With Latent Structure. [Citation Graph (0, 0)][DBLP]
    Robotics: Science and Systems, 2005, pp:81-88 [Conf]
  63. Eugene Charniak, Glenn Carroll, John Adcock, Anthony R. Cassandra, Yoshihiko Gotoh, Jeremy Katz, Michael L. Littman, John McCann
    Taggers for Parsers. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1996, v:85, n:1-2, pp:45-57 [Journal]
  64. Leslie Pack Kaelbling, Michael L. Littman, Anthony R. Cassandra
    Planning and Acting in Partially Observable Stochastic Domains. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1998, v:101, n:1-2, pp:99-134 [Journal]
  65. Stephen M. Majercik, Michael L. Littman
    Contingent planning under uncertainty via stochastic satisfiability. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2003, v:147, n:1-2, pp:119-162 [Journal]
  66. Michael L. Littman, Greg A. Keim, Noam M. Shazeer
    A probabilistic approach to solving crossword puzzles. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2002, v:134, n:1-2, pp:23-55 [Journal]
  67. 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]
  68. Giuseppe De Giacomo, Marie desJardins, Dolores Cañamero, Glenn S. Wasson, Michael L. Littman, Gerard Allwein, Kim Marriott, Bernd Meyer, Barbara Webb, Tom Con
    The AAAI Fall Symposia. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 1999, v:20, n:3, pp:87-89 [Journal]
  69. Yukio Ohsawa, Peter McBurney, Simon Parsons, Christopher A. Miller, Alan C. Schultz, Jean Scholtz, Michael A. Goodrich, Eugene Santos Jr., Benjamin Bell, Charles Lee Isbell Jr., Michael L. Littman
    AAAI-2002 Fall Symposium Series. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2003, v:24, n:1, pp:95-98 [Journal]
  70. Sebastian Thrun, Michael L. Littman
    A Review of Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2000, v:21, n:1, pp:103-105 [Journal]
  71. Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore
    Reinforcement Learning: A Survey [Citation Graph (0, 0)][DBLP]
    CoRR, 1996, v:0, n:, pp:- [Journal]
  72. Michael L. Littman, Judy Goldsmith, Martin Mundhenk
    The Computational Complexity of Probabilistic Planning [Citation Graph (0, 0)][DBLP]
    CoRR, 1998, v:0, n:, pp:- [Journal]
  73. Peter D. Turney, Michael L. Littman
    Measuring Praise and Criticism: Inference of Semantic Orientation from Association [Citation Graph (0, 0)][DBLP]
    CoRR, 2003, v:0, n:, pp:- [Journal]
  74. Peter D. Turney, Michael L. Littman, Jeffrey Bigham, Victor Shnayder
    Combining Independent Modules to Solve Multiple-choice Synonym and Analogy Problems [Citation Graph (0, 0)][DBLP]
    CoRR, 2003, v:0, n:, pp:- [Journal]
  75. Peter D. Turney, Michael L. Littman
    Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus [Citation Graph (0, 0)][DBLP]
    CoRR, 2002, v:0, n:, pp:- [Journal]
  76. Peter D. Turney, Michael L. Littman
    Learning Analogies and Semantic Relations [Citation Graph (0, 0)][DBLP]
    CoRR, 2003, v:0, n:, pp:- [Journal]
  77. Michael L. Littman, Peter Stone
    A polynomial-time Nash equilibrium algorithm for repeated games. [Citation Graph (0, 0)][DBLP]
    Decision Support Systems, 2005, v:39, n:1, pp:55-66 [Journal]
  78. Leslie Pack Kaelbling, Michael L. Littman, Andrew P. Moore
    Reinforcement Learning: A Survey. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1996, v:4, n:, pp:237-285 [Journal]
  79. Michael L. Littman, Judy Goldsmith, Martin Mundhenk
    The Computational Complexity of Probabilistic Planning. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1998, v:9, n:, pp:1-36 [Journal]
  80. 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]
  81. Peter Stone, Robert E. Schapire, Michael L. Littman, János A. Csirik, David A. McAllester
    Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2003, v:19, n:, pp:209-242 [Journal]
  82. Michael L. Littman, Stephen M. Majercik, Toniann Pitassi
    Stochastic Boolean Satisfiability. [Citation Graph (0, 0)][DBLP]
    J. Autom. Reasoning, 2001, v:27, n:3, pp:251-296 [Journal]
  83. 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]
  84. Peter D. Turney, Michael L. Littman
    Corpus-based Learning of Analogies and Semantic Relations. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2005, v:60, n:1-3, pp:251-278 [Journal]
  85. Csaba Szepesvári, Michael L. Littman
    A Unified Analysis of Value-Function-Based Reinforcement Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:8, pp:2017-2060 [Journal]
  86. Peter D. Turney, Michael L. Littman
    Measuring praise and criticism: Inference of semantic orientation from association. [Citation Graph (0, 0)][DBLP]
    ACM Trans. Inf. Syst., 2003, v:21, n:4, pp:315-346 [Journal]
  87. Alexander L. Strehl, Carlos Diuk, Michael L. Littman
    Efficient Structure Learning in Factored-State MDPs. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:645-650 [Conf]
  88. Bethany R. Leffler, Michael L. Littman, Timothy Edmunds
    Efficient Reinforcement Learning with Relocatable Action Models. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:572-577 [Conf]
  89. Thomas J. Walsh, Ali Nouri, Lihong Li, Michael L. Littman
    Planning and Learning in Environments with Delayed Feedback. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:442-453 [Conf]
  90. Ronald Parr, Christopher Painter-Wakefield, Lihong Li, Michael L. Littman
    Analyzing feature generation for value-function approximation. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:737-744 [Conf]
  91. Alexander L. Strehl, Lihong Li, Michael L. Littman
    Incremental Model-based Learners With Formal Learning-Time Guarantees. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  92. Michael L. Littman, Nishkam Ravi, Arjun Talwar, Martin Zinkevich
    An Efficient Optimal-Equilibrium Algorithm for Two-player Game Trees. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  93. Martin Zinkevich, Amy R. Greenwald, Michael L. Littman
    A hierarchy of prescriptive goals for multiagent learning. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2007, v:171, n:7, pp:440-447 [Journal]
  94. Peter D. Turney, Michael L. Littman, Jeffrey Bigham, Victor Shnayder
    Combining Independent Modules in Lexical Multiple-Choice Problems [Citation Graph (0, 0)][DBLP]
    CoRR, 2005, v:0, n:, pp:- [Journal]
  95. Håkan L. S. Younes, Michael L. Littman, David Weissman, John Asmuth
    The First Probabilistic Track of the International Planning Competition. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2005, v:24, n:, pp:851-887 [Journal]
  96. Amy R. Greenwald, Michael L. Littman
    Introduction to the special issue on learning and computational game theory. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2007, v:67, n:1-2, pp:3-6 [Journal]

  97. Potential-based Shaping in Model-based Reinforcement Learning. [Citation Graph (, )][DBLP]


  98. Efficient Learning of Action Schemas and Web-Service Descriptions. [Citation Graph (, )][DBLP]


  99. Integrating Sample-Based Planning and Model-Based Reinforcement Learning. [Citation Graph (, )][DBLP]


  100. Social reward shaping in the prisoner's dilemma. [Citation Graph (, )][DBLP]


  101. Online exploration in least-squares policy iteration. [Citation Graph (, )][DBLP]


  102. Democratic approximation of lexicographic preference models. [Citation Graph (, )][DBLP]


  103. Knows what it knows: a framework for self-aware learning. [Citation Graph (, )][DBLP]


  104. An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning. [Citation Graph (, )][DBLP]


  105. An object-oriented representation for efficient reinforcement learning. [Citation Graph (, )][DBLP]


  106. Generalizing Apprenticeship Learning across Hypothesis Classes. [Citation Graph (, )][DBLP]


  107. Classes of Multiagent Q-learning Dynamics with epsilon-greedy Exploration. [Citation Graph (, )][DBLP]


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


  109. Online Linear Regression and Its Application to Model-Based Reinforcement Learning. [Citation Graph (, )][DBLP]


  110. Multi-resolution Exploration in Continuous Spaces. [Citation Graph (, )][DBLP]


  111. Autonomous Model Learning for Reinforcement Learning. [Citation Graph (, )][DBLP]


  112. Broadening student enthusiasm for computer science with a great insights course. [Citation Graph (, )][DBLP]


  113. CORL: A Continuous-state Offset-dynamics Reinforcement Learner. [Citation Graph (, )][DBLP]


  114. A Polynomial-time Nash Equilibrium Algorithm for Repeated Stochastic Games. [Citation Graph (, )][DBLP]


  115. Learning and planning in environments with delayed feedback. [Citation Graph (, )][DBLP]


  116. Corpus-based Learning of Analogies and Semantic Relations [Citation Graph (, )][DBLP]


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