no code implementations • 28 Feb 2024 • Yu Chen, Xiangcheng Zhang, Siwei Wang, Longbo Huang
In this paper, we introduce a general framework on Risk-Sensitive Distributional Reinforcement Learning (RS-DisRL), with static Lipschitz Risk Measures (LRM) and general function approximation.
Distributional Reinforcement Learning reinforcement-learning +1
no code implementations • 14 Feb 2023 • Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
Learning Markov decision processes (MDP) in an adversarial environment has been a challenging problem.