Reinforcement Learning Papers by CMU People

(Way Out of Date!)

  • Justin Boyan, Modular Neural Networks for Learning Context-Dependent Game Strategies, August 1992 (37 pages)
  • Justin Boyan and Michael Littman, Packet routing in dynamically changing networks: A reinforcement learning approach, January 1994 (8 pages)
  • Justin Boyan and Andrew Moore, Generalization in Reinforcement Learning: Safely Approximating the Value Function, January 1995 (8 pages)
  • Lonnie Chrisman, Reinforcement Learning with Perceptual Aliasing: The Predictive Distinctions Approach , AAAI 1992 (6 pages)
  • Geoff Gordon, Online Fitted Reinforcement Learning, VFA workshop at ML-95 (3 pages)
  • Geoff Gordon, Stable Function Approximation in Dynamic Programming, ML-95 (8 pages)
  • Leslie Kaelbling, Michael Littman and Andrew Moore, Reinforcement Learning: A Survey. JAIR, 1996.
  • Sven Koenig and Reid Simmons, Complexity analysis of reinforcement learning as applied to finding shortest paths in deterministic domains, December 1992 (99 pages)
  • Tom Mitchell and Sebastian Thrun, Explanation-based neural network learning for robot control, NIPS*5, 1993 (8 pages)
  • Joseph O'Sullivan, Towards a Robot Learning Architecture, June 1993 (5 pages)

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