Meggendorfer, Tobias (2022) Risk-Aware Stochastic Shortest Path. In: AAAI-22 Technical Tracks 9 :. Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 . UNSPECIFIED, pp. 9858-9867. ISBN 1577358767
Full text not available from this repository.Abstract
We treat the problem of risk-aware control for stochastic shortest path (SSP) on Markov decision processes (MDP). Typically, expectation is considered for SSP, which however is oblivious to the incurred risk. We present an alternative view, instead optimizing conditional value-at-risk (CVaR), an established risk measure. We treat both Markov chains as well as MDP and introduce, through novel insights, two algorithms, based on linear programming and value iteration, respectively. Both algorithms offer precise and provably correct solutions. Evaluation of our prototype implementation shows that riskaware control is feasible on several moderately sized models.