受强制性开放获取政策约束的文章 - Shuyue Hu了解详情
无法在其他位置公开访问的文章：2 篇
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Learning by reusing previous advice: a memory-based teacher–student framework
C Zhu, Y Cai, S Hu, H Leung, DKW Chiu
Autonomous Agents and Multi-Agent Systems 37 (1), 14, 2023
强制性开放获取政策： 国家自然科学基金委员会
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Formal Modeling of Reinforcement Learning with Many Agents through Repeated Local Interactions
CW Leung, S Hu, HF Leung
2021 IEEE 33rd International Conference on Tools with Artificial …, 2021
强制性开放获取政策： Research Grants Council, Hong Kong
可在其他位置公开访问的文章：13 篇
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Modelling the Dynamics of Regret Minimization in Large Agent Populations: a Master Equation Approach.
Z Wang, C Mu, S Hu, C Chu, X Li
IJCAI, 534-540, 2022
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
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Emergence of punishment in social dilemma with environmental feedback
Z Wang, Z Song, C Shen, S Hu
Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 11708 …, 2023
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
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A Formal Model for Multiagent Q-Learning Dynamics on Regular Graphs.
C Chu, Y Li, J Liu, S Hu, X Li, Z Wang
IJCAI, 194-200, 2022
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
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How committed individuals shape social dynamics: a survey on coordination games and social dilemma games
C Shen, H Guo, S Hu, L Shi, Z Wang, J Tanimoto
Europhysics Letters 144 (1), 11002, 2023
强制性开放获取政策： 国家自然科学基金委员会
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Facilitating cooperation in human-agent hybrid populations through autonomous agents
H Guo, C Shen, S Hu, J Xing, P Tao, Y Shi, Z Wang
Iscience 26 (11), 2023
强制性开放获取政策： 国家自然科学基金委员会
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A q-values sharing framework for multi-agent reinforcement learning under budget constraint
C Zhu, HF Leung, S Hu, Y Cai
ACM Transactions on Autonomous and Adaptive Systems (TAAS) 15 (2), 1-28, 2021
强制性开放获取政策： 国家自然科学基金委员会, Research Grants Council, Hong Kong
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Gist trace-based learning: Efficient convention emergence from multilateral interactions
S Hu, CW Leung, HF Leung, J Liu
ACM Transactions on Autonomous and Adaptive Systems (TAAS) 16 (1), 1-20, 2022
强制性开放获取政策： Research Grants Council, Hong Kong
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The best of both worlds in network population games: Reaching consensus and convergence to equilibrium
S Hu, H Soh, G Piliouras
Advances in Neural Information Processing Systems 36, 77149-77173, 2023
强制性开放获取政策： A*Star, Singapore, National Research Foundation, Singapore
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A pair-approximation method for modelling the dynamics of multi-agent stochastic games
C Chu, Z Yuan, S Hu, C Mu, Z Wang
Proceedings of the AAAI conference on artificial intelligence 37 (5), 5565-5572, 2023
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
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Modelling the Dynamics of Multi-Agent Q-learning: The Stochastic Effects of Local Interaction and Incomplete Information.
C Leung, S Hu, H Leung
IJCAI, 384-390, 2022
强制性开放获取政策： Research Grants Council, Hong Kong
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A Theoretical Framework for Large-Scale Human-Robot Interaction with Groups of Learning Agents
N Teh, S Hu, H Soh
Companion of the 2021 ACM/IEEE International Conference on Human-Robot …, 2021
强制性开放获取政策： National Research Foundation, Singapore
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The Stochastic Evolutionary Dynamics of Softmax Policy Gradient in Games
C Leung, S Hu, H Leung
Proceedings of the 23rd International Conference on Autonomous Agents and …, 2024
强制性开放获取政策： Research Grants Council, Hong Kong
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A Successful Strategy for Multichannel Iterated Prisoner’s Dilemma
Z Wang, Z Cao, J Shi, P Zhu, S Hu, C Chu
IJCAI 2024, 2024
强制性开放获取政策： 国家自然科学基金委员会
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