Probabilistic Sequential Safety for Stochastic Dynamical Systems

In this letter, we investigate a notion of probabilistic safety for a stochastic dynamical system. Standard safety notions are based on the idea that an unsafe region of the state-space must be avoided at each instant. In contrast, we study a sequential safety notion which is based on avoiding a tuple of target regions of the state-space. The proposed safety notion is inspired by many practical systems, ranging from modeling jailbreak attacks in large language models (LLMs) to predicting hazardous chemical reactions. In solving the sequential safety problem, we solve a sequential reachability problem for a stochastic dynamical system.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-27
DOI
https://doi.org/10.48550/arxiv.2610.37311
Primary Topic
Formal Methods in Verification
Type
preprint
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preprint

Probabilistic Sequential Safety for Stochastic Dynamical Systems

Manuela L. Bujorianu, Wisniewski Rafal, Abhijit Mazumdar
1 links
arXiv (Cornell University)
Formal Methods in Verification
preprint

Probabilistic Sequential Safety for Stochastic Dynamical Systems

Manuela L. Bujorianu, Wisniewski Rafal, Abhijit Mazumdar
preprint en

Abstract

In this letter, we investigate a notion of probabilistic safety for a stochastic dynamical system. Standard safety notions are based on the idea that an unsafe region of the state-space must be avoided at each instant. In contrast, we study a sequential safety notion which is based on avoiding a tuple of target regions of the state-space. The proposed safety notion is inspired by many practical systems, ranging from modeling jailbreak attacks in large language models (LLMs) to predicting hazardous chemical reactions. In solving the sequential safety problem, we solve a sequential reachability problem for a stochastic dynamical system.

arXiv (Cornell University)
Formal Methods in Verification
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