In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

Several authors have recently developed risk-sensitive policy gradient methods<lb>that augment the standard expected cost minimization problem with a measure of<lb>variability in cost. These studies have focused on specific risk-measures, such as<lb>the variance or conditional value at risk (CVaR). In this work, we extend the pol-<lb>icy gradient method to the whole class of coherent risk measures, which is widely<lb>accepted in finance and operations research, among other fields. We consider<lb>both static and time-consistent dynamic risk measures. For static risk measures,<lb>our approach is in the spirit of policy gradient algorithms and combines a standard<lb>sampling approach with convex programming. For dynamic risk measures, our ap-<lb>proach is actor-critic style and involves explicit approximation of value function.<lb>Most importantly, our contribution presents a unified approach to risk-sensitive<lb>reinforcement learning that generalizes and extends previous results.
Policy Gradient for Coherent Risk Measures