Christopher Amato

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Jonathan P. HowRichard C. Maclaurin Professor of Aerospace Engineering, Massachusetts Institute of TechnologyVerified email at mit.edu
Frans A. OliehoekAssociate Professor at Delft University of TechnologyVerified email at tudelft.nl
Shlomo ZilbersteinProfessor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
John VianVerified email at ieee.org
Shayegan OmidshafieiChief Scientist at Field AI (previously: Google DeepMind, Google Research, MIT)Verified email at google.com
Yuchen XiaoU.S. Research Engineer, Unitree | Research Scientist, J.P. Morgan | Ph.D. Northeastern UniversityVerified email at northeastern.edu
Mykel J. KochenderferAssociate Professor, Stanford UniversityVerified email at stanford.edu
Brett DaleyUniversity of AlbertaVerified email at ualberta.ca
Nazim Kemal UreIstanbul Technical UniversityVerified email at itu.edu.tr
Miao LiuIBMVerified email at ibm.com
Jilles S. DibangoyeAssociate Professor at University of GroningenVerified email at rug.nl
Girish ChowdharyAssociate ProfessorVerified email at illinois.edu
Andrea BaiseroPhD student, Northeastern UniversityVerified email at northeastern.edu
George KonidarisBrownVerified email at cs.brown.edu
Leslie KaelblingVerified email at csail.mit.edu
Sammie KattAalto UniversityVerified email at aalto.fi
Ali AghaNASA-JPL, CaltechVerified email at jpl.nasa.gov
Matthijs T. J. SpaanDelft University of TechnologyVerified email at tudelft.nl
Xueguang LyuNortheastern UniversityVerified email at northeastern.edu
François CharpilletINRIA - LORIAVerified email at inria.fr

Christopher Amato

Other namesChris Amato

Associate Professor at Northeastern University

Verified email at ccs.neu.edu - Homepage

Artificial Intelligence Multi-Agent Systems Multi-Robot Systems Reinforcement Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A concise introduction to decentralized POMDPs FA Oliehoek, C Amato Springer International Publishing, 2016	1312	2016
Decision making under uncertainty: theory and application MJ Kochenderfer, C Amato, G Chowdhary, JP How, HJD Reynolds, ... MIT press, 2015	815	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	655	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	170	2013
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	162	2010
Learning to Teach in Cooperative Multiagent Reinforcement Learning S Omidshafiei, DK Kim, M Liu, G Tesauro, M Riemer, C Amato, ... AAAI, 2018	161	2018
Planning with Macro-Actions in Decentralized POMDPs C Amato, GD Konidaris, LP Kaelbling International Conference on Autonomous Agents and Multiagent Systems, 2014	159*	2014
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	159	2013
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	151	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	138	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	132	2015
Scalable Planning and Learning for Multiagent POMDPs C Amato, FA Oliehoek AAAI Conference on Artificial Intelligence, 1995-2002, 2015	131	2015
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	97	2016
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	96	2021
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
Learning in POMDPs with Monte Carlo Tree Search S Katt, FA Oliehoek, C Amato ICML, 2017	92	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	90	2009
Optimizing memory-bounded controllers for decentralized POMDPs C Amato, DS Bernstein, S Zilberstein Proceedings of the Twenty-Third Conference on Uncertainty in Artificial …, 2007	90*	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

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