| Temporal difference learning and TD-Gammon G Tesauro Communications of the ACM 38 (3), 58-68, 1995 | 2510 | 1995 |
| Practical issues in temporal difference learning G Tesauro Advances in neural information processing systems 4, 1991 | 1382 | 1991 |
| TD-Gammon, a self-teaching backgammon program, achieves master-level play G Tesauro Neural computation 6 (2), 215-219, 1994 | 1112 | 1994 |
| Utility functions in autonomic systems WE Walsh, G Tesauro, JO Kephart, R Das International Conference on Autonomic Computing, 2004. Proceedings., 70-77, 2004 | 598 | 2004 |
| A hybrid reinforcement learning approach to autonomic resource allocation G Tesauro, NK Jong, R Das, MN Bennani 2006 IEEE International Conference on Autonomic Computing, 65-73, 2006 | 444 | 2006 |
| Agent-human interactions in the continuous double auction R Das, JE Hanson, JO Kephart, G Tesauro International joint conference on artificial intelligence 17 (1), 1169-1178, 2001 | 355 | 2001 |
| A multi-agent systems approach to autonomic computing G Tesauro, DM Chess, WE Walsh, R Das, A Segal, I Whalley, JO Kephart, ... Proceedings of the Third International Joint Conference on Autonomous Agents …, 2004 | 348 | 2004 |
| Learning to learn without forgetting by maximizing transfer and minimizing interference M Riemer, I Cases, R Ajemian, M Liu, I Rish, Y Tu, G Tesauro arXiv preprint arXiv:1810.11910, 2018 | 333 | 2018 |
| On-line policy improvement using Monte-Carlo search G Tesauro, G Galperin Advances in Neural Information Processing Systems 9, 1996 | 308 | 1996 |
| R 3: Reinforced ranker-reader for open-domain question answering S Wang, M Yu, X Guo, Z Wang, T Klinger, W Zhang, S Chang, G Tesauro, ... Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 294 | 2018 |
| Programming backgammon using self-teaching neural nets G Tesauro Artificial Intelligence 134 (1-2), 181-199, 2002 | 271 | 2002 |
| Extending Q-learning to general adaptive multi-agent systems G Tesauro Advances in neural information processing systems 16, 2003 | 248 | 2003 |
| Neural networks for computer virus recognition GJ Tesauro, JO Kephart, GB Sorkin IEEE expert 11 (4), 5-6, 1996 | 243 | 1996 |
| Multiresolution recurrent neural networks: An application to dialogue response generation I Serban, T Klinger, G Tesauro, K Talamadupula, B Zhou, Y Bengio, ... Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 208 | 2017 |
| Analyzing complex strategic interactions in multi-agent systems WE Walsh, R Das, G Tesauro, JO Kephart AAAI-02 Workshop on Game-Theoretic and Decision-Theoretic Agents, 109-118, 2002 | 204 | 2002 |
| Reinforcement learning in autonomic computing: A manifesto and case studies G Tesauro IEEE Internet Computing 11 (1), 22-30, 2007 | 202 | 2007 |
| Coordinating multiple autonomic managers to achieve specified power-performance tradeoffs JO Kephart, H Chan, R Das, DW Levine, G Tesauro, F Rawson, C Lefurgy Fourth International Conference on Autonomic Computing (ICAC'07), 24-24, 2007 | 195 | 2007 |
| Pricing in agent economies using multi-agent Q-learning G Tesauro, JO Kephart Autonomous agents and multi-agent systems 5 (3), 289-304, 2002 | 193 | 2002 |
| A parallel network that learns to play backgammon G Tesauro, TJ Sejnowski Artificial Intelligence 39 (3), 357-390, 1989 | 192 | 1989 |
| Biologically inspired defenses against computer viruses JO Kephart, GB Sorkin, WC Arnold, DM Chess, GJ Tesauro, SR White, ... IJCAI (1), 985-996, 1995 | 188 | 1995 |
