Shapley counterfactual credits for multi-agent reinforcement learning J Li, K Kuang, B Wang, F Liu, L Chen, F Wu, J Xiao Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 58 | 2021 |
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning J Li, K Kuang, B Wang, F Liu, L Chen, C Fan, F Wu, J Xiao International Conference on Machine Learning, 12843-12856, 2022 | 20 | 2022 |
Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation J Li, K Kuang, L Li, L Chen, S Zhang, J Shao, J Xiao Proceedings of the 29th ACM International Conference on Multimedia, 3664-3672, 2021 | 16 | 2021 |
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning? S Luo, Y Li, J Li, K Kuang, F Liu, Y Shao, C Wu | 5 | 2022 |
Two heads are better than one: a simple exploration framework for efficient multi-agent reinforcement learning J Li, K Kuang, B Wang, X Li, F Wu, J Xiao, L Chen Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |