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Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environment). The advantage of these methods compared to traditional…

Logic in Computer Science · Computer Science 2010-06-29 Matthias Güdemann , Frank Ortmeier

This paper presents a novel approach for augmenting proof-based verification with performance-style analysis of the kind employed in state-of-the-art model checking tools for probabilistic systems. Quantitative safety properties usually…

Logic in Computer Science · Computer Science 2009-12-11 Ukachukwu Ndukwu

In the design of probabilistic timed systems, bounded requirements concerning behaviour that occurs within a given time, energy, or more generally cost budget are of central importance. Traditionally, such requirements have been…

Logic in Computer Science · Computer Science 2016-05-19 Ernst Moritz Hahn , Arnd Hartmanns

Probabilistic B\"uchi automata are a natural generalization of PFA to infinite words, but have been studied in-depth only rather recently and many interesting questions are still open. PBA are known to accept, in general, a class of…

Formal Languages and Automata Theory · Computer Science 2020-04-30 Christof Löding , Anton Pirogov

Since the topic emerged several years ago, work on regular model checking has mostly been devoted to the verification of state reachability and safety properties. Though it was known that linear temporal properties could also be checked…

Logic in Computer Science · Computer Science 2009-01-27 Ahmed Bouajjani , Axel Legay , Pierre Wolper

Parametric timed automata extend timed automata (Alur and Dill, 1991) in that they allow the specification of parametric bounds on the clock values. Since their introduction in 1993 by Alur, Henzinger, and Vardi, it is known that the…

Logic in Computer Science · Computer Science 2014-04-02 Karin Quaas

Probabilistic programming languages have recently gained a lot of attention, in particular due to their applications in domains such as machine learning and differential privacy. To establish invariants of interest, many such languages…

Programming Languages · Computer Science 2026-04-08 Wenjia Ye , Matías Toro , Federico Olmedo

This paper proposes to use probabilistic model checking to synthesize optimal robot policies in multi-tasking autonomous systems that are subject to human-robot interaction. Given the convincing empirical evidence that human behavior can be…

Artificial Intelligence · Computer Science 2016-11-01 Sebastian Junges , Nils Jansen , Joost-Pieter Katoen , Ufuk Topcu

Decisiveness of infinite Markov chains with respect to some (finite or infinite) target set of states is a key property that allows to compute the reachability probability of this set up to an arbitrary precision. Most of the existing works…

Formal Languages and Automata Theory · Computer Science 2023-06-01 Alain Finkel , Serge Haddad , Lina Ye

Probability Quantification (PQ) predictions of the efficacy of safety-critical protective systems is challenging. Yet, the popularity of PQ methodologies (e.g., Probabilistic Risk Assessment (PRA), Quantitative Risk Analysis (QRA) and…

Systems and Control · Electrical Eng. & Systems 2022-03-10 Martin Wortman , Ernest Kee , Pranav Kannan

Model checking is the process of deciding whether a system satisfies a given specification. Often, when the setting comprises multiple processes, the specifications are over sets of input and output signals that correspond to individual…

Logic in Computer Science · Computer Science 2020-07-24 Shaull Almagor

The emptiness and containment problems for probabilistic automata are natural quantitative generalisations of the classical language emptiness and inclusion problems for Boolean automata. It is well known that both problems are undecidable.…

Formal Languages and Automata Theory · Computer Science 2020-03-31 Laure Daviaud , Marcin Jurdziński , Ranko Lazić , Filip Mazowiecki , Guillermo A. Pérez , James Worrell

We study observation-based strategies for partially-observable Markov decision processes (POMDPs) with omega-regular objectives. An observation-based strategy relies on partial information about the history of a play, namely, on the past…

Logic in Computer Science · Computer Science 2015-05-14 Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger

We consider partially observable Markov decision processes (POMDPs) with {\omega}-regular conditions specified as parity objectives. The class of {\omega}-regular languages extends regular languages to infinite strings and provides a robust…

Logic in Computer Science · Computer Science 2013-09-12 Krishnendu Chatterjee , Martin Chmelik , Mathieu Tracol

This paper presents a probabilistic model validation methodology for nonlinear systems in time-domain. The proposed formulation is simple, intuitive, and accounts both deterministic and stochastic nonlinear systems with parametric and…

Systems and Control · Computer Science 2014-02-04 Abhishek Halder , Raktim Bhattacharya

Given its ability to analyse stochastic models ranging from discrete and continuous-time Markov chains to Markov decision processes and stochastic games, probabilistic model checking (PMC) is widely used to verify system dependability and…

Logic in Computer Science · Computer Science 2025-03-26 Radu Calinescu , Sinem Getir Yaman , Simos Gerasimou , Gricel Vázquez , Micah Bassett

Biological systems are often modeled as a system of ordinary differential equations (ODEs) with time-invariant parameters. However, cell signaling events or pharmacological interventions may alter the cellular state and induce multi-mode…

Quantitative Methods · Quantitative Biology 2020-04-28 Bing Liu

Autonomous systems are often required to operate in partially observable environments. They must reliably execute a specified objective even with incomplete information about the state of the environment. We propose a methodology to…

Artificial Intelligence · Computer Science 2020-01-14 Maxime Bouton , Jana Tumova , Mykel J. Kochenderfer

Cellular Automata are discrete--time dynamical systems on a spatially extended discrete space which provide paradigmatic examples of nonlinear phenomena. Their stochastic generalizations, i.e., Probabilistic Cellular Automata, are discrete…

Statistical Mechanics · Physics 2016-07-06 Emilio N. M. Cirillo , Francesca R. Nardi , Cristian Spitoni

We consider the problem of model--checking for Process Rewrite Systems (PRSs) in normal form. In a PRS in normal form every rewrite rule either only deals with procedure calls and procedure termination, possibly with value return, (this…

Other Computer Science · Computer Science 2007-05-23 Laura Bozzelli