| Temporal difference learning and TD-Gammon G Tesauro Communications of the ACM 38 (3), 58-68, 1995 | 3179 | 1995 |
| Practical issues in temporal difference learning G Tesauro Advances in neural information processing systems 4, 1991 | 1483 | 1991 |
| TD-Gammon, a self-teaching backgammon program, achieves master-level play G Tesauro Neural computation 6 (2), 215-219, 1994 | 1356 | 1994 |
| 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 | 896 | 2018 |
| Utility functions in autonomic systems WE Walsh, G Tesauro, JO Kephart, R Das International Conference on Autonomic Computing, 2004. Proceedings., 70-77, 2004 | 621 | 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 | 489 | 2006 |
| R3: Reinforced Ranker-Reader for Open-Domain Question Answering S Wang, M Yu, X Guo, Z Wang, T Klinger, W Zhang, S Chang, G Tesauro, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 411 | 2018 |
| 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 | 382 | 2001 |
| On-line policy improvement using Monte-Carlo search G Tesauro, G Galperin Advances in neural information processing systems 9, 1996 | 380 | 1996 |
| 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 | 369 | 2004 |
| Programming backgammon using self-teaching neural nets G Tesauro Artificial Intelligence 134 (1-2), 181-199, 2002 | 318 | 2002 |
| Diverse few-shot text classification with multiple metrics M Yu, X Guo, J Yi, S Chang, S Potdar, Y Cheng, G Tesauro, H Wang, ... arXiv preprint arXiv:1805.07513, 2018 | 308 | 2018 |
| Extending Q-learning to general adaptive multi-agent systems G Tesauro Advances in neural information processing systems 16, 2003 | 307 | 2003 |
| Neural networks for computer virus recognition GJ Tesauro, JO Kephart, GB Sorkin IEEE expert 11 (4), 5-6, 1996 | 264 | 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 | 253 | 2017 |
| Metric learning for kernel regression KQ Weinberger, G Tesauro Artificial intelligence and statistics, 612-619, 2007 | 235 | 2007 |
| 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 | 231 | 2002 |
| Biologically inspired defenses against computer viruses JO Kephart, GB Sorkin, WC Arnold, DM Chess, GJ Tesauro, SR White, ... IJCAI (1), 985-996, 1995 | 225 | 1995 |
| Pricing in agent economies using multi-agent Q-learning G Tesauro, JO Kephart Autonomous agents and multi-agent systems 5, 289-304, 2002 | 222 | 2002 |
| Dialog-based interactive image retrieval X Guo, H Wu, Y Cheng, S Rennie, G Tesauro, R Feris Advances in neural information processing systems 31, 2018 | 211 | 2018 |
