8 citations · 9 across the 7 of their papers we have counts for
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cs.AI2023
SVDE: Scalable Value-Decomposition Exploration for Cooperative Multi-Agent Reinforcement Learning
Shuhan Qi, Shuhao Zhang, Qiang Wang +3
Value-decomposition methods, which reduce the difficulty of a multi-agent system by decomposing the joint state-action space into local observation-action spaces, have become popul…
cs.AI2022
Efficient Distributed Framework for Collaborative Multi-Agent Reinforcement Learning
Shuhan Qi, Shuhao Zhang, Xiaohan Hou +3
Multi-agent reinforcement learning for incomplete information environments has attracted extensive attention from researchers. However, due to the slow sample collection and poor s…
cs.AI2021★ 1 cited
D2CFR: Minimize Counterfactual Regret with Deep Dueling Neural Network
Huale Li, Xuan Wang, Zengyue Guo +2
Counterfactual Regret Minimization (CFR)} is the popular method for finding approximate Nash equilibrium in two-player zero-sum games with imperfect information. CFR solves games b…