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Kai Shao

2 accepted papers

2025

Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics

NeurIPS 2025poster

Mean field games (MFGs) have emerged as a powerful framework for modeling interactions in large-scale multi-agent systems. Despite recent advancements in reinforcement learning (RL) for MFGs, existing methods are typically limited to finite spaces or stationary models, hindering their applicability…

Cited by 0SourceScholar
2022

On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning

ICLR 2022poster

A simple and natural algorithm for reinforcement learning (RL) is Monte Carlo Exploring Starts (MCES), where the Q-function is estimated by averaging the Monte Carlo returns, and the policy is improved by choosing actions that maximize the current estimate of the Q-function. Exploration is performed…

Cited by 28SourcePDFScholar