Risk-Averse Stochastic Shortest Path Planning

• URL: http://arxiv.org/abs/2103.14727v1
• Date: Fri, 26 Mar 2021 20:49:14 GMT
• Title: Risk-Averse Stochastic Shortest Path Planning
• Authors: Mohamadreza Ahmadi, Anushri Dixit, Joel W. Burdick, and Aaron D. Ames
• Abstract summary: We show that optimal, stationary, Markovian policies exist and can be found via a special Bellman's equation. 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.
• Score: 25.987787625028204
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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