| A concise introduction to decentralized POMDPs FA Oliehoek, C Amato Springer International Publishing, 2016 | 1384 | 2016 |
| Decision making under uncertainty: theory and application MJ Kochenderfer, C Amato, G Chowdhary, JP How, HJD Reynolds, ... MIT press, 2015 | 835 | 2015 |
| Deep Decentralized Multi-task Multi-Agent RL under Partial Observability S Omidshafiei, J Pazis, C Amato, JP How, J Vian International Conference on Machine Learning, 2681-2690, 2017 | 674 | 2017 |
| Optimally Solving Dec-POMDPs as Continuous-State MDPs JS Dibangoye, C Amato, O Buffet, F Charpillet Proceedings of the Twenty-Third International Joint Conference on Artificial …, 2013 | 178 | 2013 |
| Decentralized Control of Partially Observable Markov Decision Processes C Amato, G Chowdhary, A Geramifard, NK Ure, M Kochenderfer Proceedings of the Fifty-Second IEEE Conference on Decision and Control (CDC-13), 2013 | 170 | 2013 |
| Learning to Teach in Cooperative Multiagent Reinforcement Learning S Omidshafiei, DK Kim, M Liu, G Tesauro, M Riemer, C Amato, ... AAAI, 2018 | 166 | 2018 |
| Optimizing fixed-size stochastic controllers for POMDPs and decentralized POMDPs C Amato, DS Bernstein, S Zilberstein Autonomous Agents and Multi-Agent Systems 21 (3), 293-320, 2010 | 164 | 2010 |
| Planning with Macro-Actions in Decentralized POMDPs C Amato, GD Konidaris, LP Kaelbling International Conference on Autonomous Agents and Multiagent Systems, 2014 | 162* | 2014 |
| Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning X Lyu, Y Xiao, B Daley, C Amato Autonomous Agents and Multi-Agent Systems (AAMAS), 2021 | 160 | 2021 |
| Policy iteration for decentralized control of Markov decision processes DS Bernstein, C Amato, EA Hansen, S Zilberstein Journal of Artificial Intelligence Research 34 (1), 89, 2009 | 142 | 2009 |
| Planning for Decentralized Control of Multiple Robots Under Uncertainty C Amato, G Konidaris, G Cruz, CA Maynor, JP How, LP Kaelbling IEEE International Conference on Robotics and Automation, 2015 | 135 | 2015 |
| Scalable Planning and Learning for Multiagent POMDPs C Amato, FA Oliehoek AAAI Conference on Artificial Intelligence, 1995-2002, 2015 | 132 | 2015 |
| Safe Multi-Agent Reinforcement Learning via Shielding I Elsayed-Aly, S Bharadwaj, C Amato, R Ehlers, U Topcu, L Feng Autonomous Agents and Multi-Agent Systems (AAMAS), 2021 | 102 | 2021 |
| Policy search for multi-robot coordination under uncertainty C Amato, G Konidaris, A Anders, G Cruz, JP How, LP Kaelbling The International Journal of Robotics Research 35 (14), 1760-1778, 2016 | 98 | 2016 |
| Learning in POMDPs with Monte Carlo Tree Search S Katt, FA Oliehoek, C Amato ICML, 2017 | 93 | 2017 |
| Incremental policy generation for finite-horizon DEC-POMDPs C Amato, JS Dibangoye, S Zilberstein Proc. of the 19th Int’l Conf. on Automated Planning and Scheduling, 2-9, 2009 | 93 | 2009 |
| Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions S Omidshafiei, AA Agha–Mohammadi, C Amato, SY Liu, JP How, J Vian The International Journal of Robotics Research 36 (2), 231-258, 2017 | 92 | 2017 |
| Optimizing memory-bounded controllers for decentralized POMDPs C Amato, DS Bernstein, S Zilberstein Proceedings of the Twenty-Third Conference on Uncertainty in Artificial …, 2007 | 92* | 2007 |
| High-level reinforcement learning in strategy games. C Amato, G Shani AAMAS 10, 75-82, 2010 | 89 | 2010 |
| Online planning for target object search in clutter under partial observability Y Xiao, S Katt, A ten Pas, S Chen, C Amato 2019 International Conference on Robotics and Automation (ICRA), 8241-8247, 2019 | 86 | 2019 |
Frans A. OliehoekAssociate Professor at Delft University of Technology在 tudelft.nl 的電子郵件地址已通過驗證
