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Gerald Tesauro: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Gerald Tesauro
    Connectionist Learning of Expert Backgammon Evaluations. [Citation Graph (1, 0)][DBLP]
    ML, 1988, pp:200-206 [Conf]
  2. Amy R. Greenwald, Jeffrey O. Kephart, Gerald Tesauro
    Strategic pricebot dynamics. [Citation Graph (1, 0)][DBLP]
    ACM Conference on Electronic Commerce, 1999, pp:58-67 [Conf]
  3. Gerald Tesauro, Terrence J. Sejnowski
    A Parallel Network that Learns to Play Backgammon. [Citation Graph (1, 0)][DBLP]
    Artif. Intell., 1989, v:39, n:3, pp:357-390 [Journal]
  4. Gerald Tesauro
    Practical Issues in Temporal Difference Learning. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1992, v:8, n:, pp:257-277 [Journal]
  5. Relu Patrascu, Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
    New Approaches to Optimization and Utility Elicitation in Autonomic Computing. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:140-145 [Conf]
  6. Gerald Tesauro
    Online Resource Allocation Using Decompositional Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:886-891 [Conf]
  7. Gerald Tesauro, Jonathan Bredin
    Strategic sequential bidding in auctions using dynamic programming. [Citation Graph (0, 0)][DBLP]
    AAMAS, 2002, pp:591-598 [Conf]
  8. Gerald Tesauro, David M. Chess, William E. Walsh, Rajarshi Das, Alla Segal, Ian Whalley, Jeffrey O. Kephart, Steve R. White
    A Multi-Agent Systems Approach to Autonomic Computing. [Citation Graph (0, 0)][DBLP]
    AAMAS, 2004, pp:464-471 [Conf]
  9. Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani
    Improvement of Systems Management Policies Using Hybrid Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:783-791 [Conf]
  10. Gerald Tesauro, Rajarshi Das, William E. Walsh, Jeffrey O. Kephart
    Utility-Function-Driven Resource Allocation in Autonomic Systems. [Citation Graph (0, 0)][DBLP]
    ICAC, 2005, pp:342-343 [Conf]
  11. William E. Walsh, Gerald Tesauro, Jeffrey O. Kephart, Rajarshi Das
    Utility Functions in Autonomic Systems. [Citation Graph (0, 0)][DBLP]
    ICAC, 2004, pp:70-77 [Conf]
  12. Manu Sridharan, Gerald Tesauro
    Multi-Agent Q-Learning and Regression Trees for Automated Pricing Decisions. [Citation Graph (0, 0)][DBLP]
    ICMAS, 2000, pp:447-448 [Conf]
  13. Jeffrey O. Kephart, Gerald Tesauro
    Pseudo-convergent Q-Learning by Competitive Pricebots. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:463-470 [Conf]
  14. Manu Sridharan, Gerald Tesauro
    Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:927-934 [Conf]
  15. Gerald Tesauro
    Temporal Difference Learning of Backgammon Strategy. [Citation Graph (0, 0)][DBLP]
    ML, 1992, pp:451-457 [Conf]
  16. Rajarshi Das, James E. Hanson, Jeffrey O. Kephart, Gerald Tesauro
    Agent-Human Interactions in the Continuous Double Auction. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:1169-1187 [Conf]
  17. Jeffrey O. Kephart, Gregory B. Sorkin, William C. Arnold, David M. Chess, Gerald Tesauro, Steve R. White
    Biologically Inspired Defenses Against Computer Viruses. [Citation Graph (0, 0)][DBLP]
    IJCAI (1), 1995, pp:985-996 [Conf]
  18. Subutai Ahmad, Gerald Tesauro
    Scaling and Generalization in Neural Networks: A Case Study. [Citation Graph (0, 0)][DBLP]
    NIPS, 1988, pp:160-168 [Conf]
  19. Subutai Ahmad, Gerald Tesauro, Yu He
    Asymptotic Convergence of Backpropagation: Numerical Experiments. [Citation Graph (0, 0)][DBLP]
    NIPS, 1989, pp:606-613 [Conf]
  20. David A. Cohn, Gerald Tesauro
    Can Neural Networks Do Better Than the Vapnik-Chervonenkis Bounds? [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:911-917 [Conf]
  21. Gerald Tesauro
    Extending Q-Learning to General Adaptive Multi-Agent Systems. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  22. Gerald Tesauro
    Connectionist Learning of Expert Preferences by Comparison Training. [Citation Graph (0, 0)][DBLP]
    NIPS, 1988, pp:99-106 [Conf]
  23. Gerald Tesauro
    Practical Issues in Temporal Difference Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:259-266 [Conf]
  24. Gerald Tesauro, Gregory R. Galperin
    On-line Policy Improvement using Monte-Carlo Search. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:1068-1074 [Conf]
  25. Gerald Tesauro, Terrence J. Sejnowski
    A 'Neural' Network that Learns to Play Backgammon. [Citation Graph (0, 0)][DBLP]
    NIPS, 1987, pp:794-803 [Conf]
  26. Jakub Wejchert, Gerald Tesauro
    Neural Network Visualization. [Citation Graph (0, 0)][DBLP]
    NIPS, 1989, pp:465-472 [Conf]
  27. Gerald Tesauro
    Pricing in Agent Economies Using Neural Networks and Multi-agent Q-Learning. [Citation Graph (0, 0)][DBLP]
    Sequence Learning, 2001, pp:288-307 [Conf]
  28. James E. Hanson, Gerald Tesauro, Jeffrey O. Kephart, E. C. Snibl
    Multi-agent implementation of asymmetric protocol for bilateral negotiations. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2003, pp:224-225 [Conf]
  29. Cuihong Li, Gerald Tesauro
    A strategic decision model for multi-attribute bilateral negotiation with alternating. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2003, pp:208-209 [Conf]
  30. Gerald Tesauro, Rajarshi Das
    High-performance bidding agents for the continuous double auction. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2001, pp:206-209 [Conf]
  31. Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
    Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:89-97 [Conf]
  32. Gerald Tesauro, Jeffrey O. Kephart
    Pricing in Agent Economies Using Multi-Agent Q-Learning. [Citation Graph (0, 0)][DBLP]
    Autonomous Agents and Multi-Agent Systems, 2002, v:5, n:3, pp:289-304 [Journal]
  33. Gerald Tesauro
    Programming backgammon using self-teaching neural nets. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2002, v:134, n:1-2, pp:181-199 [Journal]
  34. Gerald Tesauro
    Temporal Difference Learning and TD-Gammon. [Citation Graph (0, 0)][DBLP]
    Commun. ACM, 1995, v:38, n:3, pp:58-68 [Journal]
  35. Gerald Tesauro
    Comments on ``Co-Evolution in the Successful Learning of Backgammon Strategy''. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:32, n:3, pp:241-243 [Journal]
  36. Jeffrey O. Kephart, Hoi Chan, Rajarshi Das, David W. Levine, Gerald Tesauro, Freeman L. Rawson III, Charles Lefurgy
    Coordinating Multiple Autonomic Managers to Achieve Specified Power-Performance Tradeoffs. [Citation Graph (0, 0)][DBLP]
    ICAC, 2007, pp:24- [Conf]
  37. Irina Rish, Gerald Tesauro
    Estimating End-to-End Performance by Collaborative Prediction with Active Sampling. [Citation Graph (0, 0)][DBLP]
    Integrated Network Management, 2007, pp:294-303 [Conf]
  38. Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani
    On the use of hybrid reinforcement learning for autonomic resource allocation. [Citation Graph (0, 0)][DBLP]
    Cluster Computing, 2007, v:10, n:3, pp:287-299 [Journal]
  39. Gerald Tesauro, Jeffrey O. Kephart
    Foresight-based pricing algorithms in agent economies. [Citation Graph (0, 0)][DBLP]
    Decision Support Systems, 2000, v:28, n:1-2, pp:49-60 [Journal]
  40. Gerald Tesauro
    Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies. [Citation Graph (0, 0)][DBLP]
    IEEE Internet Computing, 2007, v:11, n:1, pp:22-30 [Journal]

  41. Autonomic multi-agent management of power and performance in data centers. [Citation Graph (, )][DBLP]


  42. A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation. [Citation Graph (, )][DBLP]


  43. Monte-Carlo simulation balancing. [Citation Graph (, )][DBLP]


  44. Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning. [Citation Graph (, )][DBLP]


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