| Transfer learning for reinforcement learning domains: A survey. ME Taylor, P Stone Journal of Machine Learning Research 10 (7), 2009 | 2482 | 2009 |
| Deep Recurrent Q-Learning for Partially Observable MDPs. MJ Hausknecht, P Stone AAAI fall symposia 45, 141, 2015 | 2419 | 2015 |
| Multiagent systems: A survey from a machine learning perspective P Stone, M Veloso Autonomous Robots 8, 345-383, 2000 | 2083 | 2000 |
| A multiagent approach to autonomous intersection management K Dresner, P Stone Journal of artificial intelligence research 31, 591-656, 2008 | 1652 | 2008 |
| Artificial intelligence and life in 2030: the one hundred year study on artificial intelligence P Stone, R Brooks, E Brynjolfsson, R Calo, O Etzioni, G Hager, ... arXiv preprint arXiv:2211.06318, 2022 | 1205 | 2022 |
| Layered learning in multiagent systems PH Stone Carnegie Mellon University, 1998 | 1053* | 1998 |
| Multiagent traffic management: A reservation-based intersection control mechanism K Dresner, P Stone Autonomous Agents and Multiagent Systems, International Joint Conference on …, 2004 | 923 | 2004 |
| Behavioral cloning from observation F Torabi, G Warnell, P Stone arXiv preprint arXiv:1805.01954, 2018 | 890 | 2018 |
| Policy gradient reinforcement learning for fast quadrupedal locomotion N Kohl, P Stone IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 844 | 2004 |
| Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science DC Mocanu, E Mocanu, P Stone, PH Nguyen, M Gibescu, A Liotta Nature communications 9 (1), 2383, 2018 | 760 | 2018 |
| Interactively shaping agents via human reinforcement: The TAMER framework WB Knox, P Stone Proceedings of the fifth international conference on Knowledge capture, 9-16, 2009 | 658 | 2009 |
| Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork P Stone, M Veloso Artificial Intelligence 110 (2), 241-273, 1999 | 654 | 1999 |
| Curriculum learning for reinforcement learning domains: A framework and survey S Narvekar, B Peng, M Leonetti, J Sinapov, ME Taylor, P Stone Journal of Machine Learning Research 21 (181), 1-50, 2020 | 642 | 2020 |
| Autonomous agents modelling other agents: A comprehensive survey and open problems SV Albrecht, P Stone Artificial Intelligence 258, 66-95, 2018 | 627 | 2018 |
| Reinforcement learning for robocup soccer keepaway P Stone, RS Sutton, G Kuhlmann Adaptive Behavior 13 (3), 165-188, 2005 | 620 | 2005 |
| Ad hoc autonomous agent teams: Collaboration without pre-coordination P Stone, G Kaminka, S Kraus, J Rosenschein Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 1504-1509, 2010 | 504 | 2010 |
| The RoboCup synthetic agent challenge 97 H Kitano, M Tambe, P Stone, M Veloso, S Coradeschi, E Osawa, ... RoboCup-97: Robot Soccer World Cup I 1, 62-73, 1998 | 500 | 1998 |
| Outracing champion Gran Turismo drivers with deep reinforcement learning PR Wurman, S Barrett, K Kawamoto, J MacGlashan, K Subramanian, ... Nature 602 (7896), 223-228, 2022 | 496 | 2022 |
| PAC subset selection in stochastic multi-armed bandits. S Kalyanakrishnan, A Tewari, P Auer, P Stone ICML 12, 655-662, 2012 | 455 | 2012 |
| Deep reinforcement learning in parameterized action space M Hausknecht, P Stone arXiv preprint arXiv:1511.04143, 2015 | 427 | 2015 |
Manuela M. VelosoHerbert A. Simon University Professor of Computer Science, Carnegie Mellon UniversityE-mail confirmado em cs.cmu.edu
