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Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods


Jun 10, 2021
Brett Daley, Christopher Amato

* 12 pages, 6 figures, 3 tables 

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Reconciling Rewards with Predictive State Representations


Jun 07, 2021
Andrea Baisero, Christopher Amato

* IJCAI 2021 

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Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps


Jun 07, 2021
Chengguang Xu, Christopher Amato, Lawson L. S. Wong

* 21 pages, Conference on Robot Learning 2020, Boston, MA 

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Unbiased Asymmetric Actor-Critic for Partially Observable Reinforcement Learning


May 25, 2021
Andrea Baisero, Christopher Amato


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End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning


Apr 26, 2021
Mohammadreza Sharif, Deniz Erdogmus, Christopher Amato, Taskin Padir

* ICRA 2021 Camera-ready version. Source code available at https://github.com/sharif1093/dextron 

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Decentralized Reinforcement Learning for Multi-Target Search and Detection by a Team of Drones


Mar 17, 2021
Roi Yehoshua, Juan Heredia-Juesas, Yushu Wu, Christopher Amato, Jose Martinez-Lorenzo


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Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning


Feb 22, 2021
Brett Daley, Cameron Hickert, Christopher Amato

* AAMAS 2021 Extended Abstract, 3 pages, 3 figures 

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Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning


Feb 08, 2021
Xueguang Lyu, Yuchen Xiao, Brett Daley, Christopher Amato


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Safe Multi-Agent Reinforcement Learning via Shielding


Feb 02, 2021
Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato, Rüdiger Ehlers, Ufuk Topcu, Lu Feng

* 8 pages, 11 figures and 2 tables, to be published in AAMAS 2021 

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Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability


Nov 05, 2020
Hai Nguyen, Brett Daley, Xinchao Song, Christopher Amato, Robert Platt


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Expectigrad: Fast Stochastic Optimization with Robust Convergence Properties


Oct 03, 2020
Brett Daley, Christopher Amato

* 18 pages, 4 figures, 3 tables 

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Macro-Action-Based Deep Multi-Agent Reinforcement Learning


Apr 18, 2020
Yuchen Xiao, Joshua Hoffman, Christopher Amato

* 3rd Conference on Robot Learning (CoRL 2019) 

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Active Goal Recognition


Sep 24, 2019
Christopher Amato, Andrea Baisero


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Multi-Robot Deep Reinforcement Learning with Macro-Actions


Sep 19, 2019
Yuchen Xiao, Joshua Hoffman, Tian Xia, Christopher Amato


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Decentralized Likelihood Implicit Quantile Network


Jan 13, 2019
Xueguang Lu, Christopher Amato


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Bayesian Reinforcement Learning in Factored POMDPs


Nov 14, 2018
Sammie Katt, Frans Oliehoek, Christopher Amato


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Efficient Eligibility Traces for Deep Reinforcement Learning


Oct 23, 2018
Brett Daley, Christopher Amato


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Learning to Teach in Cooperative Multiagent Reinforcement Learning


Aug 31, 2018
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How


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Learning in POMDPs with Monte Carlo Tree Search


Jun 14, 2018
Sammie Katt, Frans A. Oliehoek, Christopher Amato

* Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1819-1827, 2017 

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Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems


Oct 17, 2017
Trong Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato, Jonathan How


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Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions


Aug 18, 2017
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How

* Accepted to the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) 

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Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability


Jul 13, 2017
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian

* Proceedings of the 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia, PMLR 70:2681-2690, 2017 
* Accepted to ICML 2017 

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Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces


Mar 16, 2017
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian


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Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations


Mar 16, 2017
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T. Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian


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Stick-Breaking Policy Learning in Dec-POMDPs


Nov 23, 2015
Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How


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Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions


Feb 20, 2015
Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Jonathan P. How


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Scalable Planning and Learning for Multiagent POMDPs: Extended Version


Dec 20, 2014
Christopher Amato, Frans A. Oliehoek


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Planning for Decentralized Control of Multiple Robots Under Uncertainty


Feb 12, 2014
Christopher Amato, George D. Konidaris, Gabriel Cruz, Christopher A. Maynor, Jonathan P. How, Leslie P. Kaelbling


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Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs


Feb 04, 2014
Frans Adriaan Oliehoek, Matthijs T. J. Spaan, Christopher Amato, Shimon Whiteson

* Journal Of Artificial Intelligence Research, Volume 46, pages 449-509, 2013 

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