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This paper presents LEXR, a framework for explaining the decision making of recurrent neural networks (RNNs) using a formal description language called Linear Temporal Logic (LTL). LTL is the de facto standard for the specification of…

Artificial Intelligence · Computer Science 2020-06-15 Bishwamittra Ghosh , Daniel Neider

We consider the decidability of state-to-state reachability in linear time-invariant control systems over discrete time. We analyse this problem with respect to the allowable control sets, which in general are assumed to be defined by…

Optimization and Control · Mathematics 2020-11-19 Nathanaël Fijalkow , Joël Ouaknine , Amaury Pouly , João Sousa-Pinto , James Worrell

In this paper, the problem of assessing the Finite-Time Stability (FTS) property for general nonlinear systems is considered. First, some necessary and sufficient conditions that guarantee the FTS of general nonlinear systems are provided;…

Optimization and Control · Mathematics 2023-03-02 Adriano Mele , Alfredo Pironti

Ensuring that reinforcement learning (RL) controllers satisfy safety and reliability constraints in real-world settings remains challenging: state-avoidance and constrained Markov decision processes often fail to capture trajectory-level…

Machine Learning · Computer Science 2026-04-06 Alper Kamil Bozkurt , Calin Belta , Ming C. Lin

We study the expressivity and complexity of model checking linear temporal logic with team semantics (TeamLTL). TeamLTL, despite being a purely modal logic, is capable of defining hyperproperties, i.e., properties which relate multiple…

Logic in Computer Science · Computer Science 2021-11-24 Jonni Virtema , Jana Hofmann , Bernd Finkbeiner , Juha Kontinen , Fan Yang

A specification given as a formula in linear temporal logic (LTL) defines a system by its set of traces. However, certain features such as information flow security constraints are rather modeled as so-called hyperproperties, which are sets…

Logic in Computer Science · Computer Science 2020-04-28 Martin Lück

Inevitability properties in branching temporal logics are of the syntax forall eventually \phi, where \phi is an arbitrary (timed) CTL formula. In the sense that "good things will happen", they are parallel to the "liveness" properties in…

Symbolic Computation · Computer Science 2007-05-23 Farn Wang , Geng-Dian Hwang , Fang Yu

Temporal stream logic (TSL) extends LTL with updates and predicates over arbitrary function terms. This allows for specifying data-intensive systems for which LTL is not expressive enough. In the semantics of TSL, functions and predicates…

Logic in Computer Science · Computer Science 2022-01-26 Bernd Finkbeiner , Philippe Heim , Noemi Passing

Declarative Distributed Systems (DDSs) are distributed systems grounded in logic programming. Although DDS model-checking is undecidable in general, we detect decidable cases by tweaking the data-source bounds, the message expressiveness,…

Logic in Computer Science · Computer Science 2023-08-22 Francesco Di Cosmo

Hyperproperties are properties of systems that relate different executions traces, with many applications from security to symmetry, consistency models of concurrency, etc. In recent years, different linear-time logics for specifying…

Logic in Computer Science · Computer Science 2022-07-08 Laura Bozzelli , Adriano Peron , Cesar Sanchez

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

Probabilistic model checking for systems with large or unbounded state space is a challenging computational problem in formal modelling and its applications. Numerical algorithms require an explicit representation of the state space, while…

Logic in Computer Science · Computer Science 2018-06-12 Dimitrios Milios , Guido Sanguinetti , David Schnoerr

Dynamic Bayesian networks (DBNs) are compact graphical representations used to model probabilistic systems where interdependent random variables and their distributions evolve over time. In this paper, we study the verification of the…

Artificial Intelligence · Computer Science 2025-11-14 Rajab Aghamov , Christel Baier , Joel Ouaknine , Jakob Piribauer , Mihir Vahanwala , Isa Vialard

This paper considers robot motion planning under temporal logic constraints in probabilistic maps obtained by semantic simultaneous localization and mapping (SLAM). The uncertainty in a map distribution presents a great challenge for…

Robotics · Computer Science 2016-11-17 Jie Fu , Nikolay Atanasov , Ufuk Topcu , George J. Pappas

Temporal Logic (TL) guided control problems have gained interests in recent years. By using the TL, one can specify a wide range of temporal constraints on the system and is widely used in cyber-physical systems. On the other hand, Control…

Systems and Control · Computer Science 2019-03-12 Guang Yang , Roberto Tron , Calin Belta

We propose a new abstract formalism for probabilistic timed systems, Parametric Interval Probabilistic Timed Automata, based on an extension of Parametric Timed Automata and Interval Markov Chains. In this context, we consider the…

Formal Languages and Automata Theory · Computer Science 2019-06-13 Étienne André , Benoît Delahaye , Paulin Fournier

Finite linear temporal logic ($\mathsf{LTL}_f$) is a powerful formal representation for modeling temporal sequences. We address the problem of learning a compact $\mathsf{LTL}_f$ formula from labeled traces of system behavior. We propose a…

Artificial Intelligence · Computer Science 2021-11-23 Homer Walke , Daniel Ritter , Carl Trimbach , Michael Littman

Our paper investigates the linear logic of knowledge and time LTK_r with reflexive intransitive time relation. The logic is defined semantically, -- as the set of formulas which are true at special frames with intransitive and reflexive…

Logic in Computer Science · Computer Science 2014-07-29 Alexandra Lukyanchuk , Vladimir Rybakov

This paper presents two stochastic model predictive control methods for linear time-invariant systems subject to unbounded additive uncertainties. The new methods are developed by formulating the chance constraints into deterministic form,…

Systems and Control · Electrical Eng. & Systems 2021-04-22 Fei Li , Huiping Li , Yuyao He

Many types of attacks on confidentiality stem from the nondeterministic nature of the environment that computer programs operate in (e.g., schedulers and asynchronous communication channels). In this paper, we focus on verification of…

Logic in Computer Science · Computer Science 2023-01-27 Tzu-Han Hsu , Borzoo Bonakdarpour , Bernd Finkbeiner , César Sánchez
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