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Risk-Averse Stochastic Shortest Path Planning

Ahmadi, Mohamadreza and Dixit, Anushri and Burdick, Joel W. and Ames, Aaron D. (2021) Risk-Averse Stochastic Shortest Path Planning. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20210511-082139184

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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.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/2103.14727arXivDiscussion Paper
ORCID:
AuthorORCID
Ahmadi, Mohamadreza0000-0003-1447-3012
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20210511-082139184
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210511-082139184
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109065
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:11 May 2021 17:05
Last Modified:11 May 2021 17:05

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