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Distributed automata are finite-state machines that operate on finite directed graphs. Acting as synchronous distributed algorithms, they use their input graph as a network in which identical processors communicate for a possibly infinite…

Formal Languages and Automata Theory · Computer Science 2018-12-21 Fabian Reiter

Systems of deterministic finite automata communicating by sending their states upon request are investigated, when the amount of communication is restricted. The computational power and decidability properties are studied for the case of…

Formal Languages and Automata Theory · Computer Science 2014-05-23 Henning Bordihn , Martin Kutrib , Andreas Malcher

We unify functional and logic programming by treating predicatesas functions equipped with their support: the set of inputs whose output is nonzero. Datalog, for instance, is a language of finitely supported boolean functions. Finite…

Programming Languages · Computer Science 2026-04-30 Michael Arntzenius , Max Willsey

Finite-state abstractions (a.k.a. symbolic models) present a promising avenue for the formal verification and synthesis of controllers in continuous-space control systems. These abstractions provide simplified models that capture the…

Systems and Control · Electrical Eng. & Systems 2025-02-25 Daniel Ajeleye , Majid Zamani

This paper summarizes the fundamental expressiveness, closure, and decidability properties of various finite-state automata classes with multiple input tapes. It also includes an original algorithm for the intersection of one-way…

Formal Languages and Automata Theory · Computer Science 2013-12-02 Carlo A. Furia

Implicit Computational Complexity makes two aspects implicit, by manipulating programming languages rather than models of com-putation, and by internalizing the bounds rather than using external measure. We survey how automata theory…

Logic in Computer Science · Computer Science 2015-02-05 Clément Aubert

Robust optimization is a framework for modeling optimization problems involving data uncertainty and during the last decades has been an area of active research. If we focus on linear programming (LP) problems with i) uncertain data, ii)…

Numerical Analysis · Computer Science 2017-02-15 Roberto Mínguez , Víctor Casero-Alonso

In order to work with mathematical content in computer systems, it is necessary to represent it in formal languages. Ideally, these are supported by tools that verify the correctness of the content, allow computing with it, and produce…

Logic in Computer Science · Computer Science 2020-05-27 Cezary Kaliszyk , Florian Rabe

The new finite state machine package in the mathematics software system SageMath is presented and illustrated by many examples. Several combinatorial problems, in particular digit problems, are introduced, modeled by automata and…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Clemens Heuberger , Daniel Krenn , Sara Kropf

We propose a new extension of higher-order pushdown automata, which allows to use an infinite alphabet. The new automata recognize languages of data words (instead of normal words), which beside each its letter from a finite alphabet have a…

Formal Languages and Automata Theory · Computer Science 2012-10-10 Paweł Parys

A non-deterministic recursion scheme recognizes a language of finite trees. This very expressive model can simulate, among others, higher-order pushdown automata with collapse. We show decidability of the diagonal problem for schemes. This…

Formal Languages and Automata Theory · Computer Science 2016-05-03 Lorenzo Clemente , Paweł Parys , Sylvain Salvati , Igor Walukiewicz

Predictive models are fundamental to engineering reliable software systems. However, designing conservative, computable approximations for the behavior of programs (static analyses) remains a difficult and error-prone process for modern…

Programming Languages · Computer Science 2011-05-10 David Van Horn , Matthew Might

The analysis of variance (ANOVA) decomposition offers a systematic method to understand the interaction effects that contribute to a specific decision output. In this paper we introduce Neural-ANOVA, an approach to decompose neural networks…

Machine Learning · Statistics 2025-08-01 Steffen Limmer , Steffen Udluft , Clemens Otte

Deterministic synchronous systems consisting of two finite automata running in opposite directions on a shared read-only input are studied with respect to their ability to perform reversible computations, which means that the automata are…

Formal Languages and Automata Theory · Computer Science 2023-09-07 Martin Kutrib , Andreas Malcher

This paper describes an abstract machine for linguistic formalisms that are based on typed feature structures, such as HPSG. The core design of the abstract machine is given in detail, including the compilation process from a high-level…

cmp-lg · Computer Science 2008-02-03 Shuly Wintner , Nissim Francez

We consider the value 1 problem for probabilistic automata over finite words: it asks whether a given probabilistic automaton accepts words with probability arbitrarily close to 1. This problem is known to be undecidable. However, different…

Formal Languages and Automata Theory · Computer Science 2017-09-12 Nathanaël Fijalkow

This technical note reviews sate-of-the-art algorithms for linear approximation of high-dimensional dynamical systems using low-rank dynamic mode decomposition (DMD). While repeating several parts of our article "low-rank dynamic mode…

Machine Learning · Statistics 2021-08-23 Patrick Heas , Cedric Herzet

This essay examines how automation has reconfigured mathematical proof and labor, and what might happen in the future. It discusses practical standards of proof, distinguishes between prominent forms of automation in research, provides…

History and Overview · Mathematics 2024-06-27 Rodrigo Ochigame

This paper considers finite-automata based algorithms for handling linear arithmetic with both real and integer variables. Previous work has shown that this theory can be dealt with by using finite automata on infinite words, but this…

Logic in Computer Science · Computer Science 2007-05-23 Bernard Boigelot , Sebastien Jodogne , Pierre Wolper

Learning-based 3D reconstruction has emerged as a transformative technique in autonomous driving, enabling precise modeling of environments through advanced neural representations. It has inspired pioneering solutions for vital tasks in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Liewen Liao , Weihao Yan , Wang Xu , Ming Yang , Songan Zhang , H. Eric Tseng
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