Seminář o řízení a optimalizaci – Eugene Feinberg (Stony Brook University)

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Title Dynamically Augmented CVaR for Markov Decision Processes Abstract This talk describes a new approach to optimization of Conditional Value-at-Risk (CVaR) for Markov Decision Processes (MDPs) with finite state and action sets. It introduces the Dynamically augmented CVaR (DCVaR) risk objective function and provides an algorithm for its optimization. CVaR optimization for MDPs is relevant to a specially defined Robust MDP (RMDP), in which the state space is augmented with the tail risk level. This RMDP, which we call the Dynamically augmented RMDP (DRMDP), was introduced to the literature …