Resilient Strategies for Stochastic Systems: How Much Does It Take to Break a Winning Strategy?

Fuente: arXiv
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Main Authors: Grover, Kush, Zubia, Markel, Chakraborty, Debraj, Azeem, Muqsit, Jansen, Nils, Kretinsky, Jan
Format: Preprint
Published: 2026
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author Grover, Kush
Zubia, Markel
Chakraborty, Debraj
Azeem, Muqsit
Jansen, Nils
Kretinsky, Jan
author_facet Grover, Kush
Zubia, Markel
Chakraborty, Debraj
Azeem, Muqsit
Jansen, Nils
Kretinsky, Jan
contents We study the problem of resilient strategies in the presence of uncertainty. Resilient strategies enable an agent to make decisions that are robust against disturbances. In particular, we are interested in those disturbances that are able to flip a decision made by the agent. Such a disturbance may, for instance, occur when the intended action of the agent cannot be executed due to a malfunction of an actuator in the environment. In this work, we introduce the concept of resilience in the stochastic setting and present a comprehensive set of fundamental problems. Specifically, we discuss such problems for Markov decision processes with reachability and safety objectives, which also smoothly extend to stochastic games. To account for the stochastic setting, we provide various ways of aggregating the amounts of disturbances that may have occurred, for instance, in expectation or in the worst case. Moreover, to reason about infinite disturbances, we use quantitative measures, like their frequency of occurrence.
format Preprint
id arxiv_https___arxiv_org_abs_2602_24191
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Resilient Strategies for Stochastic Systems: How Much Does It Take to Break a Winning Strategy?
Grover, Kush
Zubia, Markel
Chakraborty, Debraj
Azeem, Muqsit
Jansen, Nils
Kretinsky, Jan
Computer Science and Game Theory
Artificial Intelligence
Logic in Computer Science
We study the problem of resilient strategies in the presence of uncertainty. Resilient strategies enable an agent to make decisions that are robust against disturbances. In particular, we are interested in those disturbances that are able to flip a decision made by the agent. Such a disturbance may, for instance, occur when the intended action of the agent cannot be executed due to a malfunction of an actuator in the environment. In this work, we introduce the concept of resilience in the stochastic setting and present a comprehensive set of fundamental problems. Specifically, we discuss such problems for Markov decision processes with reachability and safety objectives, which also smoothly extend to stochastic games. To account for the stochastic setting, we provide various ways of aggregating the amounts of disturbances that may have occurred, for instance, in expectation or in the worst case. Moreover, to reason about infinite disturbances, we use quantitative measures, like their frequency of occurrence.
title Resilient Strategies for Stochastic Systems: How Much Does It Take to Break a Winning Strategy?
topic Computer Science and Game Theory
Artificial Intelligence
Logic in Computer Science
url https://arxiv.org/abs/2602.24191