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Models with intractable likelihood functions arise in areas including network analysis and spatial statistics, especially those involving Gibbs random fields. Posterior parameter es timation in these settings is termed a doubly-intractable…

Computation · Statistics 2018-10-16 Lampros Bouranis , Nial Friel , Florian Maire

The increasing prevalence of neural networks in safety-critical control systems underscores the imperative need for rigorous methods to ensure the reliability and safety of these systems. This work introduces a novel approach employing…

Optimization and Control · Mathematics 2024-03-20 Hang Zhang , Yuhao Zhang , Xiangru Xu

We propose a scalable method for forward stochastic reachability analysis for uncontrolled linear systems with affine disturbance. Our method uses Fourier transforms to efficiently compute the forward stochastic reach probability measure…

Systems and Control · Computer Science 2017-02-14 Abraham P. Vinod , Baisravan Homchaudhuri , Meeko M. K. Oishi

We consider the problem of approximating the probability mass of the set of timed paths under a continuous-time Markov chain (CTMC) that are accepted by a deterministic timed automaton (DTA). As opposed to several existing works on this…

Systems and Control · Computer Science 2013-02-04 Hongfei Fu

Employing model predictive control to systems with unbounded, stochastic disturbances poses the challenge of guaranteeing safety, i.e., repeated feasibility and stability of the closed-loop system. Especially, there are no strict repeated…

Systems and Control · Electrical Eng. & Systems 2024-10-11 Maik Pfefferkorn , Rolf Findeisen

Constraint tightening to non-conservatively guarantee recursive feasibility and stability in Stochastic Model Predictive Control is addressed. Stability and feasibility requirements are considered separately, highlighting the difference…

Systems and Control · Computer Science 2016-05-13 Matthias Lorenzen , Fabrizio Dabbene , Roberto Tempo , Frank Allgöwer

When designing optimal controllers for any system, it is often the case that the true state of the system is unknown to the controller, for example due to noisy measurements or partially observable states. Incomplete state information must…

Optimization and Control · Mathematics 2014-01-23 Kendra Lesser , Meeko Oishi

Designing provably safe control is a core problem in trustworthy autonomy. However, most prior work in this regard assumes either that the system dynamics are known or deterministic, or that the state and action space are finite,…

Robotics · Computer Science 2026-02-04 Xinhang Ma , Junlin Wu , Yiannis Kantaros , Yevgeniy Vorobeychik

Stochastic automata are a formal compositional model for concurrent stochastic timed systems, with general distributions and non-deterministic choices. Measures of interest are defined over schedulers that resolve the nondeterminism. In…

Logic in Computer Science · Computer Science 2017-10-17 Pedro R. D'Argenio , Marcus Gerhold , Arnd Hartmanns , Sean Sedwards

Motivated by the success of bounded model checking framework for finite state machines, Ouaknine and Worrell proposed a time-bounded theory of real-time verification by claiming that restriction to bounded-time recovers decidability for…

Logic in Computer Science · Computer Science 2014-08-18 Shankara Narayanan Krishna , Lakshmi Manasa , Ashutosh Trivedi

We present a method to generate a robot control strategy that maximizes the probability to accomplish a task. The task is given as a Linear Temporal Logic (LTL) formula over a set of properties that can be satisfied at the regions of a…

Optimization and Control · Mathematics 2015-03-19 Xu Chu Ding , Stephen L. Smith , Calin Belta , Daniela Rus

Recent advances in machine learning technologies and sensing have paved the way for the belief that safe, accessible, and convenient autonomous vehicles may be realized in the near future. Despite tremendous advances within this context,…

Many problems in financial engineering involve the estimation of unknown conditional expectations across a time interval. Often Least Squares Monte Carlo techniques are used for the estimation. One method that can be combined with Least…

Computational Finance · Quantitative Finance 2014-04-04 Eric Beutner , Janina Schweizer , Antoon Pelsser

This paper proposes a new Sequential Monte Carlo algorithm to perform online estimation in the context of state space models when either the transition density of the latent state or the conditional likelihood of an observation given a…

Applications · Statistics 2021-05-10 Alice Martin , Marie-Pierre Etienne , Pierre Gloaguen , Sylvain Le Corff , Jimmy Olsson

Simulator-based models are models for which the likelihood is intractable but simulation of synthetic data is possible. They are often used to describe complex real-world phenomena, and as such can often be misspecified in practice.…

Reachability analysis is a popular method to give safety guarantees for stochastic cyber-physical systems (SCPSs) that takes in a symbolic description of the system dynamics and uses set-propagation methods to compute an overapproximation…

Robotics · Computer Science 2024-07-17 Navid Hashemi , Lars Lindemann , Jyotirmoy V. Deshmukh

We define PSTCTL, a probabilistic variant of Strategic Timed CTL (STCTL), interpreted over stochastic multi-agent systems with continuous time and asynchronous execution semantics. STCTL extends TCTL with strategic operators in the style of…

Logic in Computer Science · Computer Science 2026-02-12 Wojciech Jamroga , Marta Kwiatkowska , Wojciech Penczek , Laure Petrucci , Teofil Sidoruk

There has been an increasing demand for formal methods in the design process of safety-critical synthetic genetic circuits. Probabilistic model checking techniques have demonstrated significant potential in analyzing the intrinsic…

Emerging Technologies · Computer Science 2019-01-24 Thakur Neupane , Zhen Zhang , Curtis Madsen , Hao Zheng , Chris J. Myers

Taking into account future risk is essential for an autonomously operating robot to find online not only the best but also a safe action to execute. In this paper, we build upon the recently introduced formulation of probabilistic…

Artificial Intelligence · Computer Science 2024-11-12 Andrey Zhitnikov , Vadim Indelman

Parametric timed automata (PTA) are an extension of timed automata in which clocks can be compared against parameters. The reachability problem asks for the existence of an assignment of the parameters to the non-negative integers such that…

Formal Languages and Automata Theory · Computer Science 2020-11-17 Stefan Göller , Mathieu Hilaire