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cs.LG2025
Online Bayesian Risk-Averse Reinforcement Learning
Yuhao Wang, Enlu Zhou
In this paper, we study the Bayesian risk-averse formulation in reinforcement learning (RL). To address the epistemic uncertainty due to a lack of data, we adopt the Bayesian Risk…
cs.LG2025
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate
Yifan Lin, Yuhao Wang, Enlu Zhou
Reinforcement learning provides a mathematical framework for learning-based control, whose success largely depends on the amount of data it can utilize. The efficient utilization o…