16 citations · 103 across the 24 of their papers we have counts for
4 papers · 1 filter
Theoretical Guarantees of Fictitious Discount Algorithms for Episodic Reinforcement Learning and Global Convergence of Policy Gradient Methods
Xin Guo, Anran Hu, Junzi Zhang
When designing algorithms for finite-time-horizon episodic reinforcement learning problems, a common approach is to introduce a fictitious discount factor and use stationary polici…
Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach
Haotian Gu, Xin Guo, Xiaoli Wei +1
One of the challenges for multi-agent reinforcement learning (MARL) is designing efficient learning algorithms for a large system in which each agent has only limited or partial in…
A General Framework for Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu +1
This paper presents a general mean-field game (GMFG) framework for simultaneous learning and decision-making in stochastic games with a large population. It first establishes the e…
Mean-Field Controls with Q-learning for Cooperative MARL: Convergence and Complexity Analysis
Haotian Gu, Xin Guo, Xiaoli Wei +1
Multi-agent reinforcement learning (MARL), despite its popularity and empirical success, suffers from the curse of dimensionality. This paper builds the mathematical framework to a…