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Leveraging Fully Observable Policies for Learning under Partial Observability


Nov 10, 2022
Hai Nguyen, Andrea Baisero, Dian Wang, Christopher Amato, Robert Platt

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* Accepted at the 2022 Conference on Robot Learning (CoRL), Auckland, New Zealand 

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Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning


Oct 11, 2022
Yuchen Xiao, Weihao Tan, Christopher Amato

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* arXiv admin note: substantial text overlap with arXiv:2209.10003 

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Deep Transformer Q-Networks for Partially Observable Reinforcement Learning


Jun 02, 2022
Kevin Esslinger, Robert Platt, Christopher Amato

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Hierarchical Reinforcement Learning under Mixed Observability


Apr 05, 2022
Hai Nguyen, Zhihan Yang, Andrea Baisero, Xiao Ma, Robert Platt, Christopher Amato

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* Accepted at the 15th International Workshop on the Algorithmic Foundations of Robotics (WAFR) 2022, University of Maryland, College Park. The first two authors contributed equally 

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BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs


Feb 17, 2022
Sammie Katt, Hai Nguyen, Frans A. Oliehoek, Christopher Amato

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A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning


Jan 03, 2022
Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Christopher Amato

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* To appear at Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22) 

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Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions


Dec 23, 2021
Brett Daley, Christopher Amato

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* 12 pages, 0 figures 

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Virtual Replay Cache


Dec 06, 2021
Brett Daley, Christopher Amato

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* 4 pages, 1 figure, 3 tables 

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