Christopher Amato

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 101

Top Venues

Publications

Christopher Amato
(A Partial Survey of) Decentralized, Cooperative Multi-Agent Reinforcement Learning. CoRR (2024)
Chengguang Xu, Christopher Amato, Lawson L. S. Wong
Robot Navigation in Unseen Environments using Coarse Maps. ICRA (2024)
Ayhan Alp Aydeniz, Enrico Marchesini, Christopher Amato, Kagan Tumer
Entropy Seeking Constrained Multiagent Reinforcement Learning. AAMAS (2024)
Daniel Melcer, Christopher Amato, Stavros Tripakis
Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments. AAMAS (2024)
Ethan Rathbun, Christopher Amato, Alina Oprea
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents. CoRR (2024)
Enrico Marchesini, Christopher Amato
Improving Deep Policy Gradients with Value Function Search. CoRR (2023)
Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. CoRR (2023)
Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Brett Daley, Christopher Amato
On Centralized Critics in Multi-Agent Reinforcement Learning. J. Artif. Intell. Res. 77 (2023)
Enrico Marchesini, Christopher Amato
Improving Deep Policy Gradients with Value Function Search. ICLR (2023)
Brett Daley, Martha White, Christopher Amato, Marlos C. Machado
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning. CoRR (2023)
Chengguang Xu, Hieu T. Nguyen, Christopher Amato, Lawson L. S. Wong
Vision and Language Navigation in the Real World via Online Visual Language Mapping. CoRR (2023)
Hai Nguyen, Sammie Katt, Yuchen Xiao, Christopher Amato
On-Robot Bayesian Reinforcement Learning for POMDPs. CoRR (2023)
Hai Huu Nguyen, Andrea Baisero, David Klee, Dian Wang, Robert Platt, Christopher Amato
Equivariant Reinforcement Learning under Partial Observability. CoRL (2023)
Hai Nguyen, Sammie Katt, Yuchen Xiao, Christopher Amato
On-Robot Bayesian Reinforcement Learning for POMDPs. IROS (2023)
Rohit Bokade, Xiaoning Jin, Christopher Amato
Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control. CoRR (2023)
Rohit Bokade, Xiaoning Jin, Christopher Amato
Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control. IEEE Access 11 (2023)
Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. AAMAS (2023)
Brett Daley, Martha White, Christopher Amato, Marlos C. Machado
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning. ICML (2023)
Hai Nguyen, Andrea Baisero, Dian Wang, Christopher Amato, Robert Platt
Leveraging Fully Observable Policies for Learning under Partial Observability. CoRL (2022)
Andrea Baisero, Christopher Amato
Unbiased Asymmetric Reinforcement Learning under Partial Observability. AAMAS (2022)
Andrea Baisero, Brett Daley, Christopher Amato
Asymmetric DQN for partially observable reinforcement learning. UAI (2022)
Yuchen Xiao, Weihao Tan, Christopher Amato
Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning. CoRR (2022)
Daniel Melcer, Christopher Amato, Stavros Tripakis
Shield Decentralization for Safe Multi-Agent Reinforcement Learning. NeurIPS (2022)
Sammie Katt, Hai Nguyen, Frans A. Oliehoek, Christopher Amato
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs. AAMAS (2022)
Hai Nguyen, Zhihan Yang, Andrea Baisero, Xiao Ma, Robert Platt, Christopher Amato
Hierarchical Reinforcement Learning under Mixed Observability. CoRR (2022)
Hai Nguyen, Zhihan Yang, Andrea Baisero, Xiao Ma, Robert Platt, Christopher Amato
Hierarchical Reinforcement Learning Under Mixed Observability. WAFR (2022)
Hai Nguyen, Andrea Baisero, Dian Wang, Christopher Amato, Robert Platt
Leveraging Fully Observable Policies for Learning under Partial Observability. CoRR (2022)
Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Christopher Amato
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning. AAAI (2022)
Enrico Marchesini, Christopher Amato
Safety-informed mutations for evolutionary deep reinforcement learning. GECCO Companion (2022)
Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Christopher Amato
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning. CoRR (2022)
Sammie Katt, Hai Nguyen, Frans A. Oliehoek, Christopher Amato
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs. CoRR (2022)
Yuchen Xiao, Weihao Tan, Christopher Amato
Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning. NeurIPS (2022)
Kevin Esslinger, Robert Platt, Christopher Amato
Deep Transformer Q-Networks for Partially Observable Reinforcement Learning. CoRR (2022)
Brett Daley, Christopher Amato
Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions. CoRR (2021)
Andrea Baisero, Christopher Amato
Unbiased Asymmetric Actor-Critic for Partially Observable Reinforcement Learning. CoRR (2021)
Xueguang Lyu, Yuchen Xiao, Brett Daley, Christopher Amato
Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning. AAMAS (2021)
Xueguang Lyu, Yuchen Xiao, Brett Daley, Christopher Amato
Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning. CoRR (2021)
Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato, Rüdiger Ehlers, Ufuk Topcu, Lu Feng
Safe Multi-Agent Reinforcement Learning via Shielding. CoRR (2021)
Chengguang Xu, Christopher Amato, Lawson L. S. Wong
Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps. CoRR (2021)
Roi Yehoshua, Juan Heredia Juesas, Yushu Wu, Christopher Amato, Jose A. Martinez-Lorenzo
Decentralized Reinforcement Learning for Multi-Target Search and Detection by a Team of Drones. CoRR (2021)
Brett Daley, Christopher Amato
Virtual Replay Cache. CoRR (2021)
Shuo Jiang, Christopher Amato
Multi-agent reinforcement learning with directed exploration and selective memory reuse. SAC (2021)
Mohammadreza Sharif, Deniz Erdogmus, Christopher Amato, Taskin Padir
. ICRA (2021)
Brett Daley, Christopher Amato
Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods. CoRR (2021)
Andrea Baisero, Christopher Amato
Reconciling Rewards with Predictive State Representations. IJCAI (2021)
Brett Daley, Christopher Amato
Human-Level Control without Server-Grade Hardware. CoRR (2021)
Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato, Rüdiger Ehlers, Ufuk Topcu, Lu Feng
Safe Multi-Agent Reinforcement Learning via Shielding. AAMAS (2021)
Andrea Baisero, Christopher Amato
Reconciling Rewards with Predictive State Representations. CoRR (2021)
Brett Daley, Cameron Hickert, Christopher Amato
Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning. AAMAS (2021)
Yuchen Xiao, Xueguang Lyu, Christopher Amato
Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning. CoRR (2021)
Yuchen Xiao, Xueguang Lyu, Christopher Amato
Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning. MRS (2021)
Brett Daley, Cameron Hickert, Christopher Amato
Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning. CoRR (2021)
Mohammadreza Sharif, Deniz Erdogmus, Christopher Amato, Taskin Padir
End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning. CoRR (2021)
Mohammadreza Sharif, Deniz Erdogmus, Christopher Amato, Taskin Padir
Towards End-to-End Control of a Robot Prosthetic Hand via Reinforcement Learning. BioRob (2020)
Yuchen Xiao, Joshua Hoffman, Christopher Amato
Macro-Action-Based Deep Multi-Agent Reinforcement Learning. CoRR (2020)
Brett Daley, Christopher Amato
Expectigrad: Fast Stochastic Optimization with Robust Convergence Properties. CoRR (2020)
Hai Nguyen, Brett Daley, Xinchao Song, Christopher Amato, Robert Platt
Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability. CoRR (2020)
Yuchen Xiao, Joshua Hoffman, Tian Xia, Christopher Amato
Learning Multi-Robot Decentralized Macro-Action-Based Policies via a Centralized Q-Net. ICRA (2020)
Roi Yehoshua, Christopher Amato
Hybrid Independent Learning in Cooperative Markov Games. DAI (2020)
Andrea Baisero, Christopher Amato
Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning. AAMAS (2020)
Xueguang Lyu, Christopher Amato
Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning. AAMAS (2020)
Chengguang Xu, Christopher Amato, Lawson L. S. Wong
Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps. CoRL (2020)
Hai Nguyen, Brett Daley, Xinchao Song, Christopher Amato, Robert Platt
Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability. CoRL (2020)
Yuchen Xiao, Joshua Hoffman, Tian Xia, Christopher Amato
Multi-Agent/Robot Deep Reinforcement Learning with Macro-Actions (Student Abstract). AAAI (2020)
Balint Gucsi, Danesh S. Tarapore, William Yeoh, Christopher Amato, Long Tran-Thanh
To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots. IROS (2020)
Yuchen Xiao, Joshua Hoffman, Christopher Amato
Macro-Action-Based Deep Multi-Agent Reinforcement Learning. CoRL (2019)
Christopher Amato, Andrea Baisero
Active Goal Recognition. CoRR (2019)
Yuchen Xiao, Joshua Hoffman, Tian Xia, Christopher Amato
Multi-Robot Deep Reinforcement Learning with Macro-Actions. CoRR (2019)
Brett Daley, Christopher Amato
Reconciling λ-Returns with Experience Replay. NeurIPS (2019)
Christopher Amato, John P. Dickerson
AAAI/ACM SIGAI job fair 2019: a retrospective. AI Matters 5 (1) (2019)
Yuchen Xiao, Sammie Katt, Andreas ten Pas, Shengjian Chen, Christopher Amato
Online Planning for Target Object Search in Clutter under Partial Observability. ICRA (2019)
Christopher Amato, George Dimitri Konidaris, Leslie Pack Kaelbling, Jonathan P. How
Modeling and Planning with Macro-Actions in Decentralized POMDPs. J. Artif. Intell. Res. 64 (2019)
Sammie Katt, Frans A. Oliehoek, Christopher Amato
Bayesian Reinforcement Learning in Factored POMDPs. AAMAS (2019)
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
Learning to Teach in Cooperative Multiagent Reinforcement Learning. AAAI (2019)
Christopher Amato, Haitham Bou-Ammar, Elizabeth F. Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, William F. Lawless, Francesca Rossi, Frans A. Oliehoek, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip van Allen, Kristen Brent Venable, Peter Vrancx, Shiqi Zhang
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39 (4) (2018)
Xueguang Lyu, Christopher Amato
On Improving Decentralized Hysteretic Deep Reinforcement Learning. CoRR (2018)
Zhengxing Chen, Christopher Amato, Truong-Huy D. Nguyen, Seth Cooper, Yizhou Sun, Magy Seif El-Nasr
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games. CIG (2018)
Trong Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato, Jonathan P. How
Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems. ICRA (2018)
Brett Daley, Christopher Amato
Efficient Eligibility Traces for Deep Reinforcement Learning. CoRR (2018)
Zhengxing Chen, Truong-Huy D. Nguyen, Yuyu Xu, Christopher Amato, Seth Cooper, Yizhou Sun, Magy Seif El-Nasr
The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games. RecSys (2018)
Sammie Katt, Frans A. Oliehoek, Christopher Amato
Bayesian Reinforcement Learning in Factored POMDPs. CoRR (2018)
Sammie Katt, Frans A. Oliehoek, Christopher Amato
Learning in POMDPs with Monte Carlo Tree Search. CoRR (2018)
Christopher Amato
Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning. IJCAI (2018)
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
Learning to Teach in Cooperative Multiagent Reinforcement Learning. CoRR (2018)
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces. CoRR (2017)
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions. CoRR (2017)
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. ICML (2017)
Madison Clark-Turner, Christopher Amato
COG-DICE: An Algorithm for Solving Continuous-Observation Dec-POMDPs. IJCAI (2017)
Sammie Katt, Frans A. Oliehoek, Christopher Amato
Learning in POMDPs with Monte Carlo Tree Search. ICML (2017)
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. CoRR (2017)
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian
Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations. CoRR (2017)
Shayegan Omidshafiei, Ali-Akbar Agha-Mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How, John Vian
Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions. Int. J. Robotics Res. 36 (2) (2017)
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian
Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. ICRA (2017)
Trong Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato, Jonathan P. How
Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems. CoRR (2017)
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How
Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. IROS (2017)
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian
Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. ICRA (2017)
Christopher Amato, George Dimitri Konidaris, Ariel Anders, Gabriel Cruz, Jonathan P. How, Leslie Pack Kaelbling
Policy search for multi-robot coordination under uncertainty. Int. J. Robotics Res. 35 (14) (2016)
Christopher Amato, Ofra Amir, Joanna Bryson, Barbara J. Grosz, Bipin Indurkhya, Emre Kiciman, Takashi Kido, William F. Lawless, Miao Liu, Braden McDorman, Ross Mead, Frans A. Oliehoek, Andrew Specian, Georgi Stojanov, Keiki Takadama
Reports of the AAAI 2016 Spring Symposium Series. AI Mag. 37 (4) (2016)
Miao Liu, Christopher Amato, Emily P. Anesta, John Daniel Griffith, Jonathan P. How
Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments. AAAI (2016)
Jilles Steeve Dibangoye, Christopher Amato, Olivier Buffet, François Charpillet
Optimally Solving Dec-POMDPs as Continuous-State MDPs. J. Artif. Intell. Res. 55 (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Christopher Amato