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Related papers: Parametric LTL on Markov Chains

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We investigate the problem asking whether the intersection of a context-free language (CFL) and a Petri net language (PNL) is empty. Our contribution to solve this long-standing problem which relates, for instance, to the reachability…

Formal Languages and Automata Theory · Computer Science 2015-03-19 Mohamed Faouzi Atig , Pierre Ganty

Emerging applications in autonomy require control techniques that take into account uncertain environments, communication and sensing constraints, while satisfying highlevel mission specifications. Motivated by this need, we consider a…

Systems and Control · Computer Science 2018-09-19 Suda Bharadwaj , Mohamadreza Ahmadi , Takashi Tanaka , 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

Low-rank matrix completion (LRMC) problems arise in a wide variety of applications. Previous theory mainly provides conditions for completion under missing-at-random samplings. This paper studies deterministic conditions for completion. An…

Machine Learning · Statistics 2016-10-12 Daniel L. Pimentel-Alarcón , Nigel Boston , Robert D. Nowak

Probabilistic Logic Programming (PLP) languages enable programmers to specify systems that combine logical models with statistical knowledge. The inference problem, to determine the probability of query answers in PLP, is intractable in…

Artificial Intelligence · Computer Science 2014-03-25 Arun Nampally , C. R. Ramakrishnan

We develop a central limit theorem (CLT) for a non-parametric estimator of the transition matrices in controlled Markov chains (CMCs) with finite state-action spaces. Our results establish precise conditions on the logging policy under…

Statistics Theory · Mathematics 2026-03-26 Ziwei Su , Imon Banerjee , Diego Klabjan

Runtime verification encompasses several lightweight techniques for checking whether a system's current execution satisfies a given specification. We focus on runtime verification for Linear Temporal Logic (LTL). Previous work describes…

Logic in Computer Science · Computer Science 2025-08-12 Javier Esparza , Vincent Fischer

We study the LTL model-checking in possibilistic Kripke structure using possibility measure. First, the notion of possibilistic Kripke structure and the related possibility measure are introduced, then model-checking of reachability and…

Logic in Computer Science · Computer Science 2016-09-27 Yongming Li , Lijun Li

Metric Temporal Logic (MTL) and Timed Propositional Temporal Logic (TPTL) are prominent real-time extensions of Linear Temporal Logic (LTL). In general, the satisfiability checking problem for these extensions is undecidable when both the…

Logic in Computer Science · Computer Science 2021-09-07 Shankara Narayanan Krishna , Khushraj Madnani , Manuel Mazo , Paritosh K. Pandya

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

We consider the problem of monitoring a Linear Time Logic (LTL) specification that is defined on infinite paths, over finite traces. For example, we may need to draw a verdict on whether the system satisfies or violates the property "p…

Logic in Computer Science · Computer Science 2018-04-11 Ezio Bartocci , Roderick Bloem , Dejan Nickovic , Franz Roeck

We recover the Donsker-Varadhan large deviations principle (LDP) for the empirical measure of a continuous time Markov chain on a countable (finite or infinite) state space from the joint LDP for the empirical measure and the empirical flow…

Probability · Mathematics 2013-01-01 L. Bertini , A. Faggionato , D. Gabrielli

Time-homogeneous Markov chains are often used as disease progression models in studies of cost-effectiveness and optimal decision-making. Maximum likelihood estimation of these models can be challenging when data are collected at a time…

Methodology · Statistics 2022-09-26 Duncan Ermini Leaf

The limiting probability distribution is one of the key characteristics of a Markov chain since it shows its long-term behavior. In this paper, for a higher order Markov chain, we establish some properties related to its exact limiting…

Probability · Mathematics 2026-03-20 Lixing Han , Jianhong Xu

We aim at improving reasoning on inconsistent and uncertain data. We focus on knowledge-graph data, extended with time intervals to specify their validity, as regularly found in historical sciences. We propose principles on semantics for…

Artificial Intelligence · Computer Science 2022-11-30 Victor David , Raphaël Fournier-S'niehotta , Nicolas Travers

This work extends reachability analyses based on ellipsoidal techniques to Linear Time Invariant (LTI) systems subject to an integral quadratic constraint (IQC) between the past state and disturbance signals , interpreted as an input-output…

Optimization and Control · Mathematics 2020-02-14 Paul Rousse , Pierre-Loïc Garoche , Didier Henrion

Propositional Typicality Logic (PTL) is a recently proposed logic, obtained by enriching classical propositional logic with a typicality operator capturing the most typical (alias normal or conventional) situations in which a given sentence…

Artificial Intelligence · Computer Science 2020-02-05 Richard Booth , Giovanni Casini , Thomas Meyer , Ivan Varzinczak

Consider a discrete dynamical system given by a square matrix $M \in \mathbb{Q}^{d \times d}$ and a starting point $s \in \mathbb{Q}^d$. The orbit of such a system is the infinite trajectory $\langle s, Ms, M^2s, \ldots\rangle$. Given a…

Logic in Computer Science · Computer Science 2020-07-10 Toghrul Karimov , Joël Ouaknine , James Worrell

Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic which has become a standard for expressing temporal properties of finite-state Markov chains in the context of automated model checking. In this paper, we give a…

Optimization and Control · Mathematics 2012-02-22 Federico Ramponi , Debasish Chatterjee , Sean Summers , John Lygeros

This paper studies the exponential stability of random matrix products driven by a general (possibly unbounded) state space Markov chain. It is a cornerstone in the analysis of stochastic algorithms in machine learning (e.g. for parameter…

Machine Learning · Statistics 2021-02-02 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov , Hoi-To Wai