Recent Papers:
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Automatically Designing Counterfactual Regret Minimization Algorithms for Solving Imperfect-Information Games
Kai Li, Hang Xu, Haobo Fu, Qiang Fu, Junliang Xing.
Artificial Intelligence (AI), 2024.
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Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance
Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
Neural Information Processing Systems (NeurIPS), 2024. (Corresponding Author)
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Opponent Modeling with In-context Search
Yuheng Jing, Bingyun Liu, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
Neural Information Processing Systems (NeurIPS), 2024. (Corresponding Author)
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Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent
Hang Xu, Kai Li, Bingyun Liu, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
International Joint Conference on Artificial Intelligence (IJCAI), 2024. (Corresponding Author)
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Towards Offline Opponent Modeling with In-context Learning
Yuheng Jing, Kai Li, Bingyun Liu, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
International Conference on Learning Representations (ICLR), 2024. (Corresponding Author)
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Dynamic Discounted Counterfactual Regret Minimization
Hang Xu, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
International Conference on Learning Representations (ICLR), 2024, Spotlight, Top 5%. (Corresponding Author)
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Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing
Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
AAAI Conference on Artificial Intelligence (AAAI), 2024. (Corresponding Author)
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Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
Yifan Zang, Jinmin He, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng.
Neural Information Processing Systems (NeurIPS), 2023. (Corresponding Author)
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OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research
Kai Li, Hang Xu, Enmin Zhao, Zhe Wu, Junliang Xing.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.
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Sample Efficient Reinforcement Learning Using Graph-Based Memory Reconstruction
Yongxin Kang, Enmin Zhao, Yifan Zang, Lijuan Li, Kai Li, Pin Tao, Junliang Xing.
IEEE Transactions on Artificial Intelligence (TAI), 2023.
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Sequential Cooperative Multi-Agent Reinforcement Learning
Yifan Zang, Jinmin He, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023.
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Greedy when Sure and Conservative when Uncertain about the Opponents
Haobo Fu, Ye Tian, Hongxiang Yu, Weiming Liu, Shuang Wu, Jiechao Xiong, Ying Wen, Kai Li, Junliang Xing, Qiang Fu, Wei Yang.
International Conference on Machine Learning (ICML), 2022, Spotlight.
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Actor-Critic Policy Optimization in a Large-Scale Imperfect-Information Game
Haobo Fu, Weiming Liu, Shuang Wu, Yijia Wang, Tao Yang, Kai Li, Junliang Xing, Bin Li, Bo Ma, Qiang Fu, Yang Wei.
International Conference on Learning Representations (ICLR), 2022.
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AutoCFR: Learning to Design Counterfactual Regret Minimization Algorithms
Hang Xu, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing.
AAAI Conference on Artificial Intelligence (AAAI), 2022, Oral.
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AlphaHoldem: High-Performance Artificial Intelligence for Heads-Up No-Limit Poker via End-to-End Reinforcement Learning
Enmin Zhao, Renye Yan, Jinqiu Li, Kai Li, Junliang Xing.
AAAI Conference on Artificial Intelligence (AAAI), 2022. Distinguished Paper Award!
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Exploration via State Influence Modeling
Yongxin Kang, Enmin Zhao, Kai Li, Junliang Xing.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
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Potential Driven Reinforcement Learning for Hard Exploration Tasks
Enmin Zhao, Shihong Deng, Yifan Zang, Yongxin Kang, Kai Li, Junliang Xing.
International Joint Conference on Artificial Intelligence (IJCAI), 2020.
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