Christopher Amato

Assistant Professor
  Khoury College of Computer Sciences
Northeastern University

camato at ccs dot neu dot edu


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Publications:

    2020

    • Hybrid Independent Learning in Cooperative Markov Games. Roi Yehoshua and Christopher Amato. In the Proceedings of the International Conference on Distributed Artificial Intelligence (DAI-20), October 2020. [pdf forthcoming]

    • To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots. Balint Gucsi, Danesh Tarapore, William Yeoh, Christopher Amato and Long Tran-Thanh. In the Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-20), October 2020. [pdf forthcoming]

    • Towards End-to-End Control of a Robot Prosthetic Hand via Reinforcement Learning. Mohammadreza Sharif, Deniz Erdogmus, Christopher Amato and Taskin Padir. In the Proceedings of the 8th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob-20), December 2020. [pdf forthcoming]

    • Learning Multi-Robot Decentralized Macro-Action-Based Policies via a Centralized Q-net. Yuchen Xiao, Joshua Hoffman, Tian Xia and Christopher Amato. In the Proceedings of the International Conference on Robotics and Automation (ICRA-20), May 2020. [pdf] [video]

    • Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning. Xueguang Lu and Christopher Amato. In the Proceedings of the Nineteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-20), May 2020. [pdf]

    2019

    • Reconciling ?-Returns with Experience Replay. Brett Daley and Christopher Amato. In the Proceedings of the Thirty-Third Conference on Neural Information Processing Systems (NeurIPS-19), December 2019. [pdf]

    • Macro-Action-Based Deep Multi-Agent Reinforcement Learning. Yuchen Xiao, Joshua Hoffman and Christopher Amato. In the Proceedings of the Third Conference on Robot Learning (CoRL-19), October 2019. [pdf]

    • Online Planning for Target Object Search in Clutter under Partial Observability. Yuchen Xiao, Sammie Katt, Andreas ten Pas, Shengjian Chen and Christopher Amato. In the Proceedings of the 2019 IEEE International Conference on Robotics and Automation (ICRA-19), May 2019. [pdf] [video]

    • Bayesian Reinforcement Learning in Factored POMDPs. Sammie Katt, Frans A. Oliehoek and Christopher Amato. In the Proceedings of the Eighteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-19), May 2019. [pdf]

    • Modeling and Planning with Macro-Actions in Decentralized POMDPs. Christopher Amato, George Konidaris, Jonathan P. How and Leslie P. Kaelbling. In the Journal of Artificial Intelligence Research (JAIR), vol. 64: pages 817-859, March, 2019. [pdf] [link]

    • Learning to Teach in Cooperative Multiagent Reinforcement Learning. Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell and Jonathan How. In the Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), February 2019. [arXiv link] Outstanding student paper honorable mention!

    2018

    • The Art of Drafting: A Team-Oriented Hero Recommendation System for Multiplayer Online Battle Arena Games. Zhengxing Chen, Truong-Huy D. Nguyen, Yuyu Xu, Christopher Amato, Seth Cooper, Yizhou Sun and Magy Seif El-Nasr. In the Proceedings of the ACM Conference on Recommender Systems (Recsys-18), October 2018. [pdf forthcoming]

    • Q-DeckRec: a Fast Deck Recommendation System for Collectible Card Games. Zhengxing Chen, Christopher Amato, Truong-Huy D. Nguyen, Seth Cooper, Yizhou Sun and Magy Seif El-Nasr. In the Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG-18), August 2018. [pdf forthcoming]

    • Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning. Christopher Amato. In the Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), July 2018. [pdf]

    • Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems. Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato and Jonathan P. How. In the Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA-18), May 2018. [pdf] [video]

    2017

    • Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions. Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato and Jonathan P. How. In the Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-17), September 2017. [pdf] [video]

    • Deep Decentralized Multi-Task Multi-Agent Reinforcement Learning under Partial Observability. Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How and John Vian. In the Proceedings of the Thirty-Fourth International Conference on Machine Learning (ICML-17), August 2017. [pdf] [link]

    • Learning in POMDPs with Monte Carlo Tree Search. Sammie Katt, Frans A. Oliehoek and Christopher Amato. In the Proceedings of the Thirty-Fourth International Conference on Machine Learning (ICML-17), August 2017. [pdf] [link]

    • COG-DICE: An Algorithm for Solving Continuous-Observation Dec-POMDPs. Madison Clark-Turner and Christopher Amato. In the Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17), August 2017. [pdf]

    • Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces. Shayegan Omidshafiei, Christopher Amato, Miao Liu, Jonathan P. How, John Vian. In the Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA-17), May 2017. [pdf]

    • Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations. Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian. In the Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA-17), May 2017. [pdf] [video]

    • Decentralized Control of Multi-Robot Partially Observable Markov Decision Processes using Belief Space Macro-actions. Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Shih-Yuan Liu and Jonathan P. How. In the International Journal of Robotics Research (IJRR), vol. 36, Issue 2, 2017. [pdf][link]

    • Policy Search for Multi-Robot Coordination under Uncertainty. Christopher Amato, George Konidaris, Ariel Anders, Gabriel Cruz, Jonathan P. How and Leslie P. Kaelbling. In the International Journal of Robotics Research (IJRR), vol. 35, issue 14, 2017. [pdf] [link]

    2016

    • A Concise Introduction to Decentralized POMDPs. Frans A. Oliehoek and Christopher Amato. SpringerBriefs in Intelligent Systems, Springer, 2016. [Author pre-print] [link to book website] [SpringerLink]

    • Optimally Solving Dec-POMDPs as Continuous-State MDPs. Jilles S. Dibangoye, Christopher Amato, Olivier Buffet and François Charpillet. In the Journal of Artificial Intelligence Research (JAIR), 2016. [link]

    • Graph-based Cross Entropy Method for Solving Multi-Robot Decentralized POMDPs. Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How and John Vian. In the Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA-16), May 2016. [pdf]

    • Learning for Decentralized Control of Multiagent Systems in Large Partially Observable Stochastic Environments. Miao Liu, Christopher Amato, J. Daniel Griffith, Emily Anesta and Jonathan P. How. In the Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), February 2016. [pdf] [supplementary material]

    2015

    2014

    • Dec-POMDPs as Non-Observable MDPs. Frans A. Oliehoek and Christopher Amato. Technical Report IAS-UVA-14-01, Intelligent Systems Lab, University of Amsterdam, 2014. October 2014. [pdf]

    • Decentralized Decision-Making Under Uncertainty for Multi-Robot Teams. Christopher Amato, George Konidaris, Jonathan P. How and Leslie P. Kaelbling. In Proceedings of the Future of Multiple Robot Research and its Multiple Identities at the International Conference on Intelligent Robots and Systems (IROS-14), September 2014. [pdf]

    • Combined Planning Under Uncertainty for Communication and Control in Multi-Robot Teams. Christopher Amato, George Konidaris, Jonathan P. How and Leslie P. Kaelbling. In Proceedings of the Workshop on Communication-aware Robotics: New Tools for Multi-Robot Networks, Autonomous Vehicles, and Localization (CarNet) at Robotics: Science and Systems Conference (RSS-14), July 2014. [pdf forthcoming]

    • Graph-Based Planning to Solve Multi-Agent POMDPs. Ali-akbar Agha-mohammadi, Shayegan Omidshafiei, Christopher Amato and Jonathan P. How. In Proceedings of the Workshop on Distributed Control and Estimation for Robotic Vehicle Networks at Robotics: Science and Systems Conference (RSS-14), July 2014. [pdf forthcoming]

    • Planning for Decentralized Control of Multiple Robots Under Uncertainty. Christopher Amato, George Konidaris, Gabriel Cruz, Christopher A. Maynor, Jonathan P. How and Leslie P. Kaelbling. In Proceedings of the Workshop on Planning and Robotics (PlanRob) at the Twenty-Fourth International Conference on Automated Planning and Scheduling (ICAPS-14), Portsmouth, NH, June 2014. [pdf] [arXiv link of previous version]

    • Planning with Macro-Actions in Decentralized POMDPs. Christopher Amato, George Konidaris and Leslie P. Kaelbling. In Proceedings of the Thirteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-14), May 2014. [pdf]

    • Exploiting Separability in Multi-Agent Planning with Continuous-State MDPs. Jilles S. Dibangoye, Christopher Amato, Olivier Buffet and François Charpillet. In Proceedings of the Thirteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-14), May 2014. [pdf] Won best paper!

    2013

    2012

    2011

    2010

    2009

    2008

    2007

    2006

    • Optimal Fixed-Size Controllers for Decentralized POMDPs. Christopher Amato, Daniel S. Bernstein and Shlomo Zilberstein. Proceedings of the Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM) at the Fifth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) , Future University-Hakodate, May, 2006. [pdf]

    2005

    2004