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We present a data-driven framework for strategy synthesis for partially-known switched stochastic systems. The properties of the system are specified using linear temporal logic (LTL) over finite traces (LTLf), which is as expressive as LTL…

Systems and Control · Electrical Eng. & Systems 2022-03-10 John Jackson , Luca Laurenti , Eric Frew , Morteza Lahijanian

The Latent Block Model (LBM) is a model-based method to cluster simultaneously the $d$ columns and $n$ rows of a data matrix. Parameter estimation in LBM is a difficult and multifaceted problem. Although various estimation strategies have…

Statistics Theory · Mathematics 2020-02-26 Vincent Brault , Christine Keribin , Mahendra Mariadassou

Formal theorem proving with TLA+ provides rigorous guarantees for system specifications, but constructing proofs requires substantial expertise and effort. While large language models have shown promise in automating proofs for tactic-based…

Logic in Computer Science · Computer Science 2026-03-03 Yuhao Zhou , Stavros Tripakis

Probabilistic model checking is a widely used formal verification technique to automatically verify qualitative and quantitative properties for probabilistic models. However, capturing such systems, writing corresponding properties, and…

Logic in Computer Science · Computer Science 2024-03-04 Kangfeng Ye , Fang Yan , Simos Gerasimou

The Probabilistic Computational Tree Logic (PCTL) is the main specification formalism for discrete probabilistic systems modeled by Markov chains. Despite serious research attempts, the decidability of PCTL satisfiability and validity…

Logic in Computer Science · Computer Science 2025-05-01 Miroslav Chodil , Antonín Kučera

With the increasing deployment of machine learning models in many socially sensitive tasks, there is a growing demand for reliable and trustworthy predictions. One way to accomplish these requirements is to allow a model to abstain from…

Machine Learning · Computer Science 2024-09-19 Andrea Pugnana , Lorenzo Perini , Jesse Davis , Salvatore Ruggieri

Probabilistic programming has emerged as a powerful paradigm in statistics, applied science, and machine learning: by decoupling modelling from inference, it promises to allow modellers to directly reason about the processes generating…

Machine Learning · Statistics 2019-06-10 Maria I. Gorinova , Dave Moore , Matthew D. Hoffman

Probabilistic and set-based methods are two approaches for model invalidation, parameter and state estimation. Both classes of methods use different types of data, i.e. deterministic or probabilistic data, which allow different statements…

Optimization and Control · Mathematics 2013-11-28 Stefan Streif , Didier Henrion , Rolf Findeisen

This study addresses the predictive limitation of probabilistic circuits and introduces transformations as a remedy to overcome it. We demonstrate this limitation in robotic scenarios. We motivate that independent component analysis is a…

Machine Learning · Statistics 2023-10-09 Tom Schierenbeck , Vladimir Vutov , Thorsten Dickhaus , Michael Beetz

This paper proposes a specification-guided framework for control of nonlinear systems with linear temporal logic (LTL) specifications. In contrast with well-known abstraction-based methods, the proposed framework directly characterizes the…

Systems and Control · Electrical Eng. & Systems 2022-05-03 Yinan Li , Zhibing Sun , Jun Liu

Autoformalisation, the task of expressing informal mathematical statements in formal language, is often viewed as a direct translation process. This, however, disregards a critical preceding step: conjecturing. Many mathematical problems…

Computation and Language · Computer Science 2025-10-15 Jasivan Alex Sivakumar , Philipp Borchert , Ronald Cardenas , Gerasimos Lampouras

Background: Automated code summarisation supports program comprehension and documentation, yet the relative strengths and limitations of deterministic (heuristic-based) and probabilistic (LLM-based) pipelines remain unclear. Aims: This…

Software Engineering · Computer Science 2026-05-22 Najam Nazar , Christoph Treude

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

Large language models (LLMs) exhibit failure modes on seemingly trivial tasks. We propose a formalisation of LLM interaction using a deterministic multi-tape Turing machine, where each tape represents a distinct component: input characters,…

Computation and Language · Computer Science 2026-02-20 Magnus Boman

The recent progress in large language models (LLMs), especially the invention of chain-of-thought prompting, has made it possible to automatically answer questions by stepwise reasoning. However, when faced with more complicated problems…

Artificial Intelligence · Computer Science 2023-10-06 Ning Miao , Yee Whye Teh , Tom Rainforth

This paper studies motion planning of a mobile robot under uncertainty. The control objective is to synthesize a {finite-memory} control policy, such that a high-level task specified as a Linear Temporal Logic (LTL) formula is satisfied…

Robotics · Computer Science 2017-10-24 Meng Guo , Michael M. Zavlanos

We introduce a new translation from linear temporal logic (LTL) to deterministic Emerson-Lei automata, which are omega-automata with a Muller acceptance condition symbolically expressed as a Boolean formula. The richer acceptance condition…

Formal Languages and Automata Theory · Computer Science 2017-09-08 David Müller , Salomon Sickert

In this communication, we resolve a longstanding open question in the probabilistic verification of infinite-state systems. We show that model checking {\it stateless probabilistic pushdown systems (pBPA)} against {\it probabilistic…

Logic in Computer Science · Computer Science 2025-07-02 Deren Lin , Tianrong Lin

In this paper we consider a nondeterministic computation by deterministic multi-head 2-way automata having a read-only access to an auxiliary memory. The memory contains additional data (a guess) and computation is successful iff it is…

Computational Complexity · Computer Science 2008-11-18 M. N. Vyalyi

The determinization of a nondeterministic B\"uchi automaton (NBA) is a fundamental construction of automata theory, with applications to probabilistic verification and reactive synthesis. The standard determinization constructions, such as…

Formal Languages and Automata Theory · Computer Science 2022-06-29 Yong Li , Andrea Turrini , Weizhi Feng , Moshe Y. Vardi , Lijun Zhang