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Andrew G. Barto: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Alicia P. Wolfe, Andrew G. Barto
    Decision Tree Methods for Finding Reusable MDP Homomorphisms. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  2. Richard C. Yee, Sharad Saxena, Paul E. Utgoff, Andrew G. Barto
    Explaining Temporal Differences to Create Useful Concepts for Evaluating States. [Citation Graph (0, 0)][DBLP]
    AAAI, 1990, pp:882-888 [Conf]
  3. Anders Jonsson, Andrew G. Barto
    A causal approach to hierarchical decomposition of factored MDPs. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:401-408 [Conf]
  4. George Konidaris, Andrew G. Barto
    Autonomous shaping: knowledge transfer in reinforcement learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:489-496 [Conf]
  5. Amy McGovern, Andrew G. Barto
    Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:361-368 [Conf]
  6. Robert Moll, Theodore J. Perkins, Andrew G. Barto
    Machine Learning for Subproblem Selection. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:615-622 [Conf]
  7. Theodore J. Perkins, Andrew G. Barto
    Lyapunov-Constrained Action Sets for Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:409-416 [Conf]
  8. Marc Pickett, Andrew G. Barto
    PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:506-513 [Conf]
  9. Jette Randløv, Andrew G. Barto, Michael T. Rosenstein
    Combining Reinforcement Learning with a Local Control Algorithm. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:775-782 [Conf]
  10. Balaraman Ravindran, Andrew G. Barto
    Relativized Options: Choosing the Right Transformation. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:608-615 [Conf]
  11. Özgür Simsek, Alicia P. Wolfe, Andrew G. Barto
    Identifying useful subgoals in reinforcement learning by local graph partitioning. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:816-823 [Conf]
  12. Özgür Simsek, Andrew G. Barto
    Using relative novelty to identify useful temporal abstractions in reinforcement learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  13. Özgür Simsek, Andrew G. Barto
    An intrinsic reward mechanism for efficient exploration. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:833-840 [Conf]
  14. Vijaykumar Gullapalli, Andrew G. Barto, Roderic A. Grupen
    Learning Admittance Mappings for Force-Guided Assembly. [Citation Graph (0, 0)][DBLP]
    ICRA, 1994, pp:2633-2638 [Conf]
  15. Theodore J. Perkins, Andrew G. Barto
    Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:242-247 [Conf]
  16. Balaraman Ravindran, Andrew G. Barto
    SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2003, pp:1011-1018 [Conf]
  17. Michael T. Rosenstein, Andrew G. Barto
    Robot Weightlifting By Direct Policy Search. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:839-846 [Conf]
  18. Oliver G. Selfridge, Richard S. Sutton, Andrew G. Barto
    Training and Tracking in Robotics. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1985, pp:670-672 [Conf]
  19. Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
    Deictic Option Schemas. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:1023-1028 [Conf]
  20. George Konidaris, Andrew G. Barto
    Building Portable Options: Skill Transfer in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:895-900 [Conf]
  21. Kimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto
    Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels. [Citation Graph (0, 0)][DBLP]
    Intelligent Tutoring Systems, 2006, pp:453-462 [Conf]
  22. 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]
  23. Andrew G. Barto, Michael O. Duff
    Monte Carlo Matrix Inversion and Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:687-694 [Conf]
  24. Andrew G. Barto, James C. Houk
    A Predictive Switching Model of Cerebellar Movement Control. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:138-144 [Conf]
  25. Andrew G. Barto, Richard S. Sutton, Christopher J. C. H. Watkins
    Sequential Decision Probelms and Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1989, pp:686-693 [Conf]
  26. Robert H. Crites, Andrew G. Barto
    An Actor/Critic Algorithm that is Equivalent to Q-Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:401-408 [Conf]
  27. Robert H. Crites, Andrew G. Barto
    Improving Elevator Performance Using Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:1017-1023 [Conf]
  28. Michael O. Duff, Andrew G. Barto
    Local Bandit Approximation for Optimal Learning Problems. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:1019-1025 [Conf]
  29. Vijaykumar Gullapalli, Andrew G. Barto
    Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:695-702 [Conf]
  30. Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein
    Reinforcement Learning for Mixed Open-loop and Closed-loop Control. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:1026-1032 [Conf]
  31. Anders Jonsson, Andrew G. Barto
    Automated State Abstraction for Options using the U-Tree Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:1054-1060 [Conf]
  32. Michael Kositsky, Andrew G. Barto
    The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:43-50 [Conf]
  33. Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton
    Learning Instance-Independent Value Functions to Enhance Local Search. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:1017-1023 [Conf]
  34. Jeffrey F. Monaco, David G. Ward, Andrew G. Barto
    Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  35. Ron Papka, James P. Callan, Andrew G. Barto
    Text-Based Information Retrieval Using Exponentiated Gradient Descent. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:3-9 [Conf]
  36. Satinder P. Singh, Andrew G. Barto, Nuttapong Chentanez
    Intrinsically Motivated Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  37. 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]
  38. George Konidaris, Andrew G. Barto
    An Adaptive Robot Motivational System. [Citation Graph (0, 0)][DBLP]
    SAB, 2006, pp:346-356 [Conf]
  39. Balaraman Ravindran, Andrew G. Barto
    Model Minimization in Hierarchical Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    SARA, 2002, pp:196-211 [Conf]
  40. Özgür Simsek, Andrew G. Barto
    Learning Skills in Reinforcement Learning Using Relative Novelty. [Citation Graph (0, 0)][DBLP]
    SARA, 2005, pp:367-374 [Conf]
  41. Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
    Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. [Citation Graph (0, 0)][DBLP]
    Machine Learning: From Theory to Applications, 1993, pp:175-202 [Conf]
  42. 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]
  43. Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
    Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. [Citation Graph (0, 0)][DBLP]
    Cognitive Science, 1991, v:15, n:2, pp:219-250 [Journal]
  44. Michael Kositsky, Andrew G. Barto
    The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:44, n:, pp:889-895 [Journal]
  45. Andrew G. Barto
    A Note on Pattern Reproduction in Tessellation Structures. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1978, v:16, n:3, pp:445-455 [Journal]
  46. Theodore J. Perkins, Andrew G. Barto
    Lyapunov Design for Safe Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:803-832 [Journal]
  47. Anders Jonsson, Andrew G. Barto
    Causal Graph Based Decomposition of Factored MDPs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2259-2301 [Journal]
  48. Steven J. Bradtke, Andrew G. Barto
    Linear Least-Squares Algorithms for Temporal Difference Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:22, n:1-3, pp:33-57 [Journal]
  49. Robert H. Crites, Andrew G. Barto
    Elevator Group Control Using Multiple Reinforcement Learning Agents. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:33, n:2-3, pp:235-262 [Journal]
  50. Amy McGovern, J. Eliot B. Moss, Andrew G. Barto
    Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:49, n:2-3, pp:141-160 [Journal]
  51. Andrew G. Barto, Andrew H. Fagg, Nathan Sitkoff, James C. Houk
    A Cerebellar Model of Timing and Prediction in the Control of Reaching. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:3, pp:565-594 [Journal]
  52. Michael T. Rosenstein, Andrew G. Barto, Richard E. A. Van Emmerik
    Learning at the level of synergies for a robot weightlifter. [Citation Graph (0, 0)][DBLP]
    Robotics and Autonomous Systems, 2006, v:54, n:8, pp:706-717 [Journal]
  53. Anders Jonsson, Andrew G. Barto
    Active Learning of Dynamic Bayesian Networks in Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
    SARA, 2007, pp:273-284 [Conf]

  54. Repairing Disengagement With Non-Invasive Interventions. [Citation Graph (, )][DBLP]


  55. Efficient Skill Learning using Abstraction Selection. [Citation Graph (, )][DBLP]


  56. Skill Characterization Based on Betweenness. [Citation Graph (, )][DBLP]


  57. Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks. [Citation Graph (, )][DBLP]


  58. Linear systems analysis of the relationship between firing of deep cerebellar neurons and the classically conditioned nictitating membrane response in rabbits. [Citation Graph (, )][DBLP]


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