Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback

Yu Chen, Yihan Du, Pihe Hu +3

Risk-sensitive reinforcement learning (RL) aims to optimize policies that balance the expected reward and risk. In this paper, we present a novel risk-sensitive RL framework that e…