Gerald Tesauro

Janusz Marecki, Gerald Tesauro, Richard Segal: Playing repeated Stackelberg games with unknown opponents. AAMAS 2012: 821-828

Joseph P. Bigus, Ching-Hua Chen-Ritzo, Keith Hermiz, Gerald Tesauro, Robert Sorrentino: Applying a framework for healthcare incentives simulation. Winter Simulation Conference 2012: 80

Gerald Tesauro, V. T. Rajan, Richard Segal: Bayesian Inference in Monte-Carlo Tree Search. CoRR abs/1203.3519 (2012)

Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh: Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation. CoRR abs/1212.2443 (2012)

Gerald Tesauro, V. T. Rajan, Richard Segal: Bayesian Inference in Monte-Carlo Tree Search. UAI 2010: 580-588

David Silver, Gerald Tesauro: Monte-Carlo simulation balancing. ICML 2009: 119

Rajarshi Das, Jeffrey O. Kephart, Charles Lefurgy, Gerald Tesauro, David W. Levine, Hoi Chan: Autonomic multi-agent management of power and performance in data centers. AAMAS (Industry Track) 2008: 107-114

Irina Rish, Gerald Tesauro: Active Collaborative Prediction with Maximum Margin Matrix Factorization. ISAIM 2008

Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani: On the use of hybrid reinforcement learning for autonomic resource allocation. Cluster Computing 10(3): 287-299 (2007)

Gerald Tesauro: Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies. IEEE Internet Computing 11(1): 22-30 (2007)

Kilian Q. Weinberger, Gerald Tesauro: Metric Learning for Kernel Regression. Journal of Machine Learning Research - Proceedings Track 2: 612-619 (2007)

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. ICAC 2007: 24

Irina Rish, Gerald Tesauro: Estimating End-to-End Performance by Collaborative Prediction with Active Sampling. Integrated Network Management 2007: 294-303

Gerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey O. Kephart, David Levine, Freeman L. Rawson III, Charles Lefurgy: Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning. NIPS 2007

Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani: Improvement of Systems Management Policies Using Hybrid Reinforcement Learning. ECML 2006: 783-791

Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani: A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation. ICAC 2006: 65-73

Relu Patrascu, Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh: New Approaches to Optimization and Utility Elicitation in Autonomic Computing. AAAI 2005: 140-145

Gerald Tesauro: Online Resource Allocation Using Decompositional Reinforcement Learning. AAAI 2005: 886-891

Gerald Tesauro, Rajarshi Das, William E. Walsh, Jeffrey O. Kephart: Utility-Function-Driven Resource Allocation in Autonomic Systems. ICAC 2005: 342-343

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. AAMAS 2004: 464-471

William E. Walsh, Gerald Tesauro, Jeffrey O. Kephart, Rajarshi Das: Utility Functions in Autonomic Systems. ICAC 2004: 70-77

Gerald Tesauro: Extending Q-Learning to General Adaptive Multi-Agent Systems. NIPS 2003

Cuihong Li, Gerald Tesauro: A strategic decision model for multi-attribute bilateral negotiation with alternating. ACM Conference on Electronic Commerce 2003: 208-209

James E. Hanson, Gerald Tesauro, Jeffrey O. Kephart, E. C. Snibl: Multi-agent implementation of asymmetric protocol for bilateral negotiations. ACM Conference on Electronic Commerce 2003: 224-225

Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh: Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation. UAI 2003: 89-97

Gerald Tesauro, Jeffrey O. Kephart: Pricing in Agent Economies Using Multi-Agent Q-Learning. Autonomous Agents and Multi-Agent Systems 5(3): 289-304 (2002)

Gerald Tesauro: Programming backgammon using self-teaching neural nets. Artif. Intell. 134(1-2): 181-199 (2002)

Gerald Tesauro, Jonathan Bredin: Strategic sequential bidding in auctions using dynamic programming. AAMAS 2002: 591-598

Rajarshi Das, James E. Hanson, Jeffrey O. Kephart, Gerald Tesauro: Agent-Human Interactions in the Continuous Double Auction. IJCAI 2001: 1169-1187

Gerald Tesauro: Pricing in Agent Economies Using Neural Networks and Multi-agent Q-Learning. Sequence Learning 2001: 288-307

Gerald Tesauro, Rajarshi Das: High-performance bidding agents for the continuous double auction. ACM Conference on Electronic Commerce 2001: 206-209

Gerald Tesauro, Jeffrey O. Kephart: Foresight-based pricing algorithms in agent economies. Decision Support Systems 28(1-2): 49-60 (2000)

Manu Sridharan, Gerald Tesauro: Multi-Agent Q-Learning and Regression Trees for Automated Pricing Decisions. ICMAS 2000: 447-448

Jeffrey O. Kephart, Gerald Tesauro: Pseudo-convergent Q-Learning by Competitive Pricebots. ICML 2000: 463-470

Manu Sridharan, Gerald Tesauro: Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions. ICML 2000: 927-934

Amy Greenwald, Jeffrey O. Kephart, Gerald Tesauro: Strategic pricebot dynamics. ACM Conference on Electronic Commerce 1999: 58-67

Gerald Tesauro: Comments on "Co-Evolution in the Successful Learning of Backgammon Strategy". Machine Learning 32(3): 241-243 (1998)

Gerald Tesauro, Gregory R. Galperin: On-line Policy Improvement using Monte-Carlo Search. NIPS 1996: 1068-1074

Gerald Tesauro: Temporal Difference Learning and TD-Gammon. Commun. ACM 38(3): 58-68 (1995)

Jeffrey O. Kephart, Gregory B. Sorkin, William C. Arnold, David M. Chess, Gerald Tesauro, Steve R. White: Biologically Inspired Defenses Against Computer Viruses. IJCAI (1) 1995: 985-996

Gerald Tesauro, David S. Touretzky, Todd K. Leen (Eds.): Advances in Neural Information Processing Systems 7, [NIPS Conference, Denver, Colorado, USA, 1994]. MIT Press 1995

Gerald Tesauro: TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play. Neural Computation 6(2): 215-219 (1994)

Jack D. Cowan, Gerald Tesauro, Joshua Alspector (Eds.): Advances in Neural Information Processing Systems 6, [7th NIPS Conference, Denver, Colorado, USA, 1993]. Morgan Kaufmann 1994, isbn 1-55860-322-0

Gerald Tesauro: Practical Issues in Temporal Difference Learning. Machine Learning 8: 257-277 (1992)

David A. Cohn, Gerald Tesauro: How Tight Are the Vapnik-Chervonenkis Bounds? Neural Computation 4(2): 249-269 (1992)

Gerald Tesauro: Temporal Difference Learning of Backgammon Strategy. ML 1992: 451-457

Jakub Wejchert, Gerald Tesauro: Visualizing processes in neural networks. IBM Journal of Research and Development 35(1): 244-253 (1991)

Gerald Tesauro: Practical Issues in Temporal Difference Learning. NIPS 1991: 259-266

David A. Cohn, Gerald Tesauro: Can Neural Networks Do Better Than the Vapnik-Chervonenkis Bounds? NIPS 1990: 911-917

Gerald Tesauro, Terrence J. Sejnowski: A Parallel Network that Learns to Play Backgammon. Artif. Intell. 39(3): 357-390 (1989)

Jakub Wejchert, Gerald Tesauro: Neural Network Visualization. NIPS 1989: 465-472

Subutai Ahmad, Gerald Tesauro, Yu He: Asymptotic Convergence of Backpropagation: Numerical Experiments. NIPS 1989: 606-613

Gerald Tesauro: Connectionist Learning of Expert Backgammon Evaluations. ML 1988: 200-206

Gerald Tesauro: Connectionist Learning of Expert Preferences by Comparison Training. NIPS 1988: 99-106

Subutai Ahmad, Gerald Tesauro: Scaling and Generalization in Neural Networks: A Case Study. NIPS 1988: 160-168

Gerald Tesauro, Terrence J. Sejnowski: A 'Neural' Network that Learns to Play Backgammon. NIPS 1987: 794-803