A Caltech Library Service

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. In: 2021 60th IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 5199-5204. ISBN 978-1-6654-3659-5.

[img] PDF - Submitted Version
See Usage Policy.


Use this Persistent URL to link to this item:


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:Book Section
Related URLs:
URLURL TypeDescription Paper
Ahmadi, Mohamadreza0000-0003-1447-3012
Ames, Aaron D.0000-0003-0848-3177
Additional Information:© 2021 IEEE.
Record Number:CaltechAUTHORS:20210511-082139184
Persistent URL:
Official Citation:M. Ahmadi, A. Dixit, J. W. Burdick and A. D. Ames, "Risk-Averse Stochastic Shortest Path Planning," 2021 60th IEEE Conference on Decision and Control (CDC), 2021, pp. 5199-5204, doi: 10.1109/CDC45484.2021.9683527
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109065
Deposited By: Tony Diaz
Deposited On:11 May 2021 17:05
Last Modified:16 Feb 2022 17:58

Repository Staff Only: item control page