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cs.LG2024
q-exponential family for policy optimization
Lingwei Zhu, Haseeb Shah, Han Wang +2
Policy optimization methods benefit from a simple and tractable policy parametrization, usually the Gaussian for continuous action spaces. In this paper, we consider a broader poli…
cs.LG2024
A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization
Yudong Luo, Yangchen Pan, Han Wang +2
Reinforcement learning algorithms utilizing policy gradients (PG) to optimize Conditional Value at Risk (CVaR) face significant challenges with sample inefficiency, hindering their…