Publications

Preprint

Siyang Wu*, Tonghan Wang*, Chenghao Li, Yang Hu, Chongjie Zhang. Containerized Distributed Value-Based Multi-Agent Reinforcement Learning. Under Review, 2021. [arXiv]
Heng Dong*, Tonghan Wang*, Jiayuan Liu, Chi Han, Chongjie Zhang. Birds of a Feather Flock Together: A Close Look at Cooperation Emergence via Multi-Agent RL. Under Review, 2021. [Website] [Code] [arXiv]
Hangtian Jia, Yujing Hu, Yingfeng Chen, Chunxu Ren, Tangjie Lv, Changjie Fan, Chongjie Zhang. Fever Basketball: A Complex, Flexible, and Asynchronized Sports Game Environment for Multi-agent Reinforcement Learning. Under Review, 2020. [arXiv]
Chenghao Li, Xiaoteng Ma, Chongjie Zhang, Jun Yang, Li Xia and Qianchuan Zhao. SOAC: The Soft Option Actor-Critic Architecture. Under Review, 2020. [arXiv]

2023

Jianhao Wang*, Jin Zhang*, Haozhe Jiang, Junyu Zhang, Liwei Wang, Chongjie Zhang. Offline Meta Reinforcement Learning with In-Distribution Online Adaptation. International Conference on Machine Learning (ICML), 2023.

Heng Dong, Junyu Zhang, Tonghan Wang, Chongjie Zhang. Symmetry-Aware Robot Design with Structured Subgroups. International Conference on Machine Learning (ICML), 2023.

Rui Yang, LIN Yong, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang. What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL? International Conference on Machine Learning (ICML), 2023.

Hao Hu, Yiqin Yang, Qianchuan Zhao, Chongjie Zhang. The Provable Benefit of Unsupervised Data Sharing for Offline Reinforcement Learning. International Conference on Learning Representations (ICLR), 2023. [PDF]

Yiqin Yang, Hao Hu, Wenzhe Li, Siyuan Li, Jun Yang, Qianchuan Zhao, Chongjie Zhang. Flow to Control: Offline Reinforcement Learning with Lossless Primitive Discovery. AAAI Conference on Artificial Intelligence (AAAI), 2023. [PDF]

2022

[Alphabetical Order] Yipeng Kang, Tonghan Wang, Xiaoran Wu, Qianlan Yang, Chongjie Zhang. Non-Linear Coordination Graphs. Advances in Neural Information Processing Systems (NeurIPS), 2022. [Spotlight Paper] [PDF]
Mingyang Liu*, Chengjie Wu*, Qihan Liu, Yansen Jing, Jun Yang, Pingzhong Tang, Chongjie Zhang. Safe Opponent-Exploitation Subgame Refinement. Advances in Neural Information Processing Systems (NeurIPS), 2022. [PDF]
Rui Yang, Chenjia Bai, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang, Lei Han. RORL: Robust Offline Reinforcement Learning via Conservative Smoothing. Advances in Neural Information Processing Systems (NeurIPS), 2022. [Spotlight Paper] [PDF]
Heng Dong*, Tonghan Wang*, Jiayuan Liu, Chongjie Zhang. Low-Rank Modular Reinforcement Learning via Muscle Synergy. Advances in Neural Information Processing Systems (NeurIPS), 2022. [PDF]
Jin Zhang, Siyuan Li, Chongjie Zhang. CUP: Critic-Guided Policy Reuse. Advances in Neural Information Processing Systems (NeurIPS), 2022. [Spotlight Paper] [PDF]
Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Liang Bin, Chelsea Finn, Chongjie Zhang. Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), 2022. [PDF]
Hao Hu*, Yiqin Yang*, Qianchuan Zhao, Chongjie Zhang. On the Role of Discount Factor in Offline Reinforcement Learning. International Conference on Machine Learning (ICML), 2022. [PDF]
Qianlan Yang*, Weijun Dong*, Zhizhou Ren*, Jianhao Wang, Tonghan Wang, Chongjie Zhang. Self-Organized Polynomial-Time Coordination Graphs. International Conference on Machine Learning (ICML), 2022. [Code] [arxiv]
Li Wang, Yujing Hu, Yupeng Zhang, Weixun Wang, Chongjie Zhang, Yang Gao, Jianye Hao, Tangjie Lv, Changjie Fan. Individual Reward Assisted Multi-Agent Reinforcement Learning. International Conference on Machine Learning (ICML), 2022.
Mingyang Liu*, Chengjie Wu*, Qihan Liu, Yansen Jing, Jun Yang, Pingzhong Tang, Chongjie Zhang. Safe Opponent-Exploitation Subgame Refinement. ICLR Workshop on Gamification and Multiagent Solutions, 2022. [PDF]
Lei Yuan*, Chenghe Wang*, Jianhao Wang, Fuxiang Zhang, Feng Chen, Cong Guan, Zongzhang Zhang, Chongjie Zhang, Yang Yu. Multi-Agent Concentrative Coordination with Decentralized Task Representation. International Joint Conference on Artificial Intelligence (IJCAI), 2022.
Jiahan Cao*, Lei Yuan*, Jianhao Wang, Shaowei Zhang, Chongjie Zhang, Yang Yu, De-Chuan Zhan. LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammates. SCIENCE CHINA Information Sciences, 2022. [arXiv]
Siyuan Li, Jin Zhang, Jianhao Wang, Yang Yu, Chongjie Zhang. Active Hierarchical Exploration with Stable Subgoal Representation Learning. International Conference on Learning Representations (ICLR), 2022. [arXiv] [Code]
Tonghan Wang*, Liang Zeng*, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang. Context-Aware Sparse Deep Coordination Graphs. International Conference on Learning Representations (ICLR), 2022. [Spotlight Paper] [arXiv] [Code]
Rui Yang, Yiming Lu, Wenzhe Li, Hao Sun, Meng Fang, Yali Du, Xiu Li, Lei Han, Chongjie Zhang. Rethinking Goal-Conditioned Supervised Learning and Its Connection to Offline RL. International Conference on Learning Representations (ICLR), 2022. [Code] [PDF]
Xiaoteng Ma* , Yiqin Yang* , Hao Hu* , Qihan Liu , Jun Yang , Chongjie Zhang, Qianchuan Zhao, Bin Liang. Offline Reinforcement Learning with Value-based Episodic Memory. International Conference on Learning Representations (ICLR), 2022. [arxiv]
Lei Yuan*， Jianhao Wang*, Fuxiang Zhang, Chenghe Wang, Zongzhang Zhang, Yang Yu, Chongjie Zhang. Multi-Agent Incentive Communication via Decentralized Teammate Modeling. AAAI Conference on Artificial Intelligence (AAAI), 2022 [Code] [PDF]

2021

Chenghao Li, Chengjie Wu, Tonghan Wang, Jun Yang, Qianchuan Zhao and Chongjie Zhang. Celebrating Diversity in Shared Multi-Agent Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), 2021. [Website] [Code] [PDF]
Jianhao Wang*, Wenzhe Li*, Haozhe Jiang, Guangxiang Zhu, Siyuan Li, Chongjie Zhang. Offline Reinforcement Learning with Reverse Model-based Imagination. Advances in Neural Information Processing Systems (NeurIPS), 2021. [Website] [Code] [PDF]
Lulu Zheng*, Jiarui Chen*, Jianhao Wang, Jiamin He, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao, Chongjie Zhang. Episodic Multi-agent Reinforcement Learning with Curiosity-driven Exploration. Advances in Neural Information Processing Systems (NeurIPS), 2021. [Code] [PDF]
Zhizhou Ren, Guangxiang Zhu, Hao Hu, Beining Han, Jianglun Chen, Chongjie Zhang. On the Estimation Bias in Double Q-Learning. Advances in Neural Information Processing Systems (NeurIPS), 2021. [Code] [PDF]
Jianhao Wang*, Zhizhou Ren*, Beining Han, Jianing Ye, and Chongjie Zhang. Towards Understanding Linear Value Decomposition in Cooperative Multi-Agent Q-Learning. Advances in Neural Information Processing Systems (NeurIPS), 2021. [PDF]
Yao Mu, Yuzheng Zhuang, Bin Wang, Guangxiang Zhu, Wulong Liu, Jianyu Chen, Ping Luo, Shengbo Eben Li, Chongjie Zhang, Jianye HAO. Model-Based Reinforcement Learning via Imagination with Derived Memory. Advances in Neural Information Processing Systems (NeurIPS), 2021. [PDF]
Jin Zhang*, Jianhao Wang*, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan and Chongjie Zhang. MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration. International Conference on Machine Learning (ICML), 2021. [Code] [PDF]
Hao Hu, Jianing Ye, Zhizhou Ren, Guangxiang Zhu, and Chongjie Zhang. Generalizable Episodic Memory for Deep Reinforcement Learning. International Conference on Machine Learning (ICML), 2021. [Code] [PDF]
Zhaorong Wang, Meng Wang, Jingqi Zhang, Yingfeng Chen, Chongjie Zhang. Reward-Constrained Behavior Cloning. International Joint Conference on Artificial Intelligence (IJCAI), 2021.
Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson and Chongjie Zhang. RODE: Learning Roles to Decompose Multi-Agent Tasks. International Conference on Learning Representations (ICLR), 2021. [Website] [Code] [PDF]
Jianhao Wang*, Zhizhou Ren*, Terry Liu, Yang Yu and Chongjie Zhang. QPLEX: Duplex Dueling Multi-Agent Q-Learning. International Conference on Learning Representations (ICLR), 2021. [Website] [Code] [PDF]
Yihan Wang*, Beining Han*, Tonghan Wang*, Heng Dong and Chongjie Zhang. Off-Policy Multi-Agent Decomposed Policy Gradients. International Conference on Learning Representations (ICLR), 2021. [Website] [Code] [PDF]
Siyuan Li*, Lulu Zheng*, Jianhao Wang and Chongjie Zhang. Learning Subgoal Representations with Slow Dynamics. International Conference on Learning Representations (ICLR), 2021. [Website] [Code] [PDF]

2020

Guangxiang Zhu*, Minghao Zhang*, Honglak Lee and Chongjie Zhang. Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), 2020.
Yipeng Kang, Tonghan Wang and Gerard de Melo. Incorporating Pragmatic Reasoning Communication into Emergent Language. Advances in Neural Information Processing Systems (NeurIPS), 2020 (Spotlight). [PDF]
Tonghan Wang, Heng Dong, Victor Lesser, and Chongjie Zhang. ROMA: Multi-Agent Reinforcement Learning with Emergent Roles. International Conference on Machine Learning (ICML), 2020. [Website] [Code] [PDF]
Yaohui Guo, Chongjie Zhang and X. Jessie Yang. Modeling Trust Dynamics in Human-robot Teaming: A Bayesian Inference Approach. Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020. [PDF]
Tonghan Wang*, Jianhao Wang*, Chongyi Zheng, Chongjie Zhang. Learning Nearly Decomposable Value Functions via Communication Minimization. International Conference on Learning Representations (ICLR), 2020. [Spotlight Paper] [Website] [Code] [PDF]
Tonghan Wang*, Jianhao Wang*, Yi Wu, Chongjie Zhang. Influence-Based Multi-Agent Exploration. International Conference on Learning Representations (ICLR), 2020. [Website] [Code] [PDF]
Guangxiang Zhu*, Zichuan Lin*, Guangwen Yang, Chongjie Zhang. Episodic Reinforcement Learning with Associated Memory. International Conference on Learning Representations (ICLR), 2020. [PDF]
Guangxiang Zhu*, Jianhao Wang*, Zhizhou Ren*, Chongjie Zhang. Object-Oriented Dynamics Learning through Multi-Level Abstraction. AAAI Conference on Artificial Intelligence (AAAI), 2020. [PDF] [arXiv]

2019

Siyuan Li*, Rui Wang*, Minxue Tang, Chongjie Zhang. Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards. (NeurIPS), 2019. [PDF][arXiv]
Tianpei Yang, Jianye Hao, Zhaopeng Meng, Chongjie Zhang, Yan Zheng, Ze Zheng. Efficiently Detecting and Optimally Responding Towards Sophisticated Opponents. Proc. of the 28th International Joint Conference on Artificial Intelligence (IJCAI) , 2019. [arXiv]
Xinliang Song, Tonghan Wang, Chongjie Zhang. Convergence of Multi-Agent Learning with a Finite Step Size in General-Sum Games. Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) ,2019. [PDF]
Siyuan Li, Fangda Gu, Guangxiang Zhu, and Chongjie Zhang. Context-Aware Policy Reuse. AAMAS 2019: International Conference on Autonomous Agents and MultiAgent Systems. [PDF] [arXiv]
Tianpei Yang, Jianye Hao, Zhaopeng Meng, Chongjie Zhang, Yan Zheng, Ze Zheng Bayes-ToMoP: A Fast Detection and Best Response Algorithm Towards Sophisticated Opponents. Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) , 2019. [PDF] [arXiv]

2018

Guangxiang Zhu*, Jianhao Wang*, Zhizhou Ren*, Chongjie Zhang. Object-Oriented Dynamics Learning through Multi-Level Abstraction. Deep Reinforcement Learning Workshop, NeurIPS , 2018. [PDF]
Guangxiang Zhu, Zhiao Huang, Chongjie Zhang. Object-Oriented Dynamics Predictor. Advances in Neural Information Processing Systems (NeurIPS), 2018. [PDF] [Supplementary] [Code] [arXiv]
Chenlan Wang, Chongjie Zhang, X. Jessie Yang. Automation Reliability and Trust: A Bayesian Inference Approach. Proceedings of the 62nd Human Factors and Ergonomics Society Annual Meeting (HFES) , 202-206, 2018. [Best Student Paper 3rd Prize, HFES CEDM-TG]. [PDF]
Changhoon Kim, Mengyuan Zhang, Chongjie Zhang, X. Jessie Yang. Trust Dynamics in Sequential Decision Making. Proceedings of the 62nd Human Factors and Ergonomics Society Annual Meeting (HFES), 165-166, 2018. [PDF]
Siyuan Li, Chongjie Zhang. An Optimal Online Method of Selecting Source Policies for Reinforcement Learning. AAAI Conference on Artificial Intelligence (AAAI), 2018. [PDF]

2017

Ramya Ramakrishnan, Chongjie Zhang, Julie A. Shah. Perturbation Training for Human-Robot Teams. Journal of Artificial Intelligence Research (JAIR), 2017. [PDF]
Dan Garant, Bruno Da Silva, Victor Lesser, Chongjie Zhang. Context-Based Concurrent Experience Sharing in Multiagent Systems. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017. [PDF] [arXiv]

2016 & Before

Chongjie Zhang, Julie A. Shah. Co-Optimizing Task and Motion Planning. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016. [PDF]
Chongjie Zhang, Julie A. Shah. Co-Optimization Multi-Agent Placement with Task Assignment and Scheduling. International Joint Conference on Artificial Intelligence (IJCAI), 2016. [PDF]
Chongjie Zhang, Julie A. Shah. On Fairness in Decision-Making under Uncertainty: Definitions, Computation, and Comparison. AAAI Conference on Artificial Intelligence (AAAI), 2015. [PDF]
Chongjie Zhang, Julie A. Shah. Fairness in Multi-Agent Sequential Decision-Making. Advances in Neural Information Processing Systems (NIPS), 2014. [PDF]
Nguyen Duc Thien, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein, Chongjie Zhang. Decentralized Multi-Agent Reinforcement Learning in Average-Reward Dynamic DCOPs. AAAI Conference on Artificial Intelligence (AAAI), 2014. [PDF]
Nguyen, Duc Thien, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein, Chongjie Zhang. Decentralized Multi-Agent Reinforcement Learning in Average-Reward Dynamic DCOPs (Extended Abstract). International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014. [PDF]
Chongjie Zhang, Victor Lesser. Coordinating Multi-Agent Reinforcement Learning with Limited Communication. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2013. [PDF]
Xiangbin Zhu, Chongjie Zhang, Victor Lesser. Combining Dynamic Reward Shaping and Action Shaping for Coordinating Multi-Agent Learning. IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), 2013. [PDF]
Dan Corkill, Chongjie Zhang, Bruno da Silva, Yoonheui Kim, Xiaoqin (Shelley) Zhang, Victor Lesser. Biasing the Behavior of Organizationally Adept Agents (Extended Abstract). International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2013. [PDF]
Chongjie Zhang, Victor Lesser. Coordinating Multi-Agent Learning for Decentralized POMDPs. International Workshop on Multiagent Sequential Decision Making Under Uncertainty (MSDM), 2012. [PDF]
Dan Corkill, Chongjie Zhang, Bruno da Silva, Yoonheui Kim, Xiaoqin (Shelley) Zhang, Victor Lesser. Using Annotated Guidelines to Influence the Behavior of Organizationally Adept Agents. International Workshop on Coordination, Organization, Institutions, and Norms (COIN@AAMAS), 2012. [PDF]
Xiaoqin Shelley Zhang, Sungwook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek Green, Jinhong K Guo, Ugur Kuter, Geoff Levine, Reid L MacTavish, Daniel McFarlane, James R Michaelis, Hala Mostafa, Bhavesh Shrestha, Zhexuan Song, Ethan B Trewhitt, Huzaifa Zafar, Chongjie Zhang, et al. An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. ACM Transactions on Intelligent Systems and Technology (TIST), 2012. [PDF]
Chongjie Zhang, Victor Lesser. Coordinated Multi-Agent Reinforcement Learning in Networked Distributed POMDPs. AAAI Conference on Artificial Intelligence (AAAI), 2011. [PDF]
Daniel Corkill, Edmund Durfee, Victor Lesser, Huzaifa Zafar, Chongjie Zhang. Organizationally Adept Agents. International Workshop on Coordination, Organization, Institutions and Norms in Agent Systems (COIN@AAMAS 2011), 2011. [PDF]
Chongjie Zhang. Scaling Multi-Agent Learning in Complex Environments. Ph.D. Dissertation, 2011. [PDF]
Chongjie Zhang, Victor Lesser. Multi-Agent Learning with Policy Prediction. AAAI Conference on Artificial Intelligence (AAAI), 2010. [PDF]
Chongjie Zhang, Victor Lesser, Sherief Abdallah. Self-Organization for Coordinating Decentralized Reinforcement Learning. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2010. [PDF]
Chongjie Zhang and Victor Lesser, Prashant Shenoy. A Multi-Agent Learning Approach to Online Distributed Resource Allocation. International Joint Conference on Artificial Intelligence (IJCAI), 2009. [PDF]
Chongjie Zhang, Victor Lesser, Sherief Abdallah. Integrating Organizational Control into Multi-Agent Learning. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2009. [PDF]
Xiaoqin Shelley Zhang, Sungwook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek Green, Jinhong K Guo, Ugur Kuter, Geoff Levine, Reid L MacTavish, Daniel McFarlane, James R Michaelis, Hala Mostafa, Bhavesh Shrestha, Zhexuan Song, Ethan B Trewhitt, Huzaifa Zafar, Chongjie Zhang, et al. An Ensemble Learning and Problem-Solving Architecture for Airspace Management. Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2009. [PDF]
Chongjie Zhang, Victor Lesser, Sherief Abdallah. Efficient Multi-Agent Reinforcement Learning through Automated Supervision (Short Paper). International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2008. [PDF]
Chongjie Zhang, Chirag Dekate, Gabrielle Allen, Ian Kelley, Jon MacLaren. An Application Portal for Collaborative Coastal Modeling. Concurrency and Computation: Practice and Experience, 2007. [PDF]
Chongjie Zhang, Ian Kelley, Gabrielle Allen. Grid Portal Solutions: A Comparison of GridPortlets and OGCE. Concurrency and Computation: Practice and Experience, 2007. [PDF]
Gabrielle Allen, Promita Chakraborty, Dayong Huang, Zhou Lei, John Lewis, Christopher White, Xiaoxi Xu, Chongjie Zhang. A Workflow Approach to Designed Reservoir Study. Workshop on Workflows in Support of Large-Scale Science (WORKS), 2007. [PDF]
Jon MacLaren, Gabrielle Allen, Chirag Dekate, Dayong Huang, Andrei Hutanu, Chongjie Zhang. Shelter from the Storm: Building a Safe Archive in a Hostile World. Lecture Notes in Computer Science, 2005. [PDF]
Chongjie Zhang, Chirag Dekate, Gabrielle Allen, Ian Kelley, Jon MacLaren. An Application Portal for Collaborative Coastal Modeling. International Workshop on Grid Computing Environments (GCE), 2005. (Best Paper Award)
Chongjie Zhang, Ian Kelley, Gabrielle Allen. Grid Portal Solutions: A Comparison of GridPortlets and OGCE. International Workshop on Grid Computing Environments (GCE), 2005.