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- W4297791417 abstract "We consider the stochastic shortest path planning problem in MDPs, i.e., the problem of designing policies that ensure reaching a goal state from a given initial state with minimum accrued cost. In order to account for rare but important realizations of the system, we consider a nested dynamic coherent risk total cost functional rather than the conventional risk-neutral total expected cost. Under some assumptions, we show that optimal, stationary, Markovian policies exist and can be found via a special Bellman's equation. We propose a computational technique based on difference convex programs (DCPs) to find the associated value functions and therefore the risk-averse policies. A rover navigation MDP is used to illustrate the proposed methodology with conditional-value-at-risk (CVaR) and entropic-value-at-risk (EVaR) coherent risk measures." @default.
- W4297791417 created "2022-10-01" @default.
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- W4297791417 date "2021-03-26" @default.
- W4297791417 modified "2023-09-26" @default.
- W4297791417 title "Risk-Averse Stochastic Shortest Path Planning" @default.
- W4297791417 doi "https://doi.org/10.48550/arxiv.2103.14727" @default.
- W4297791417 hasPublicationYear "2021" @default.
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