On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk

In order to model risk aversion in reinforcement learning, an emerging line of research adapts familiar algorithms to optimize coherent risk functionals, a class that includes conditional value-at-risk (CVaR). Because optimizing the coherent risk is difficult in Markov decision processes, recent wor...

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Bibliographische Detailangaben

Hauptverfasser:	Huang, Audrey, Leqi, Liu, Lipton, Zachary C, Azizzadenesheli, Kamyar
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Statistics - Machine Learning
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