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We study the problem of verification and synthesis of robust control barrier functions (CBF) for control-affine polynomial systems with bounded additive uncertainty and convex polynomial constraints on the control. We first formulate robust…

Optimization and Control · Mathematics 2023-07-25 Shucheng Kang , Yuxiao Chen , Heng Yang , Marco Pavone

Today's propositional satisfiability (SAT) solvers are extremely powerful and can be used as an efficient back-end for solving NP-complete problems. However, many fundamental problems in knowledge representation and reasoning are located at…

Computational Complexity · Computer Science 2016-07-04 Ronald de Haan , Stefan Szeider

In this work we investigate the computational complexity of the satisfiability problem of sub-fragments of the Bernays-Schoenfinkel class of first-order logic, also known as EPR (Effectively Propositional). While Bernays-Schoenfinkel is…

Logic in Computer Science · Computer Science 2026-02-19 Leroy Chew , Mikoláš Janota , Miroslav Olšák , Martin Suda

Given a relational specification R(X, Y), where X and Y are sequences of input and output variables, we wish to synthesize each output as a function of the inputs such that the specification holds. This is called the Boolean functional…

Logic in Computer Science · Computer Science 2017-03-07 S. Akshay , Supratik Chakraborty , Ajith K. John , Shetal Shah

Optimization is a key task in a number of applications. When the set of feasible solutions under consideration is of combinatorial nature and described in an implicit way as a set of constraints, optimization is typically NP-hard.…

Artificial Intelligence · Computer Science 2014-10-27 Daniel Le Berre , Emmanuel Lonca , Pierre Marquis

An automaton is partially ordered if the only cycles in its transition diagram are self-loops. The expressivity of partially ordered NFAs (poNFAs) can be characterized by the Straubing-Th\'erien hierarchy. Level 3/2 is recognized by poNFAs,…

Formal Languages and Automata Theory · Computer Science 2017-04-27 Tomáš Masopust , Markus Krötzsch

This is the latest in a series of articles aimed at exploring the relationship between the complexity classes of P and NP. In the previous papers, we have proved that the sat CNF problem is polynomially reduced to the problem of finding a…

Computational Complexity · Computer Science 2023-11-01 Stepan G. Margaryan

Functional graphs (FGs) model the graph structures used to analyse the behaviour of functions from a discrete set to itself. In turn, such functions are used to study real complex phenomena evolving in time. As the systems involved can be…

Dynamical Systems · Mathematics 2024-04-05 François Doré , Enrico Formenti , Antonio E. Porreca , Sara Riva

The reactive synthesis problem is to compute a system satisfying a given specification in temporal logic. Bounded synthesis is the approach to bound the maximum size of the system that we accept as a solution to the reactive synthesis…

Logic in Computer Science · Computer Science 2018-03-28 Peter Faymonville , Bernd Finkbeiner , Markus N. Rabe , Leander Tentrup

The theory of Total Function NP (TFNP) and its subclasses says that, even if one is promised an efficiently verifiable proof exists for a problem, finding this proof can be intractable. Despite the success of the theory at showing…

Quantum Physics · Physics 2025-06-23 Marco Aldi , Sevag Gharibian , Dorian Rudolph

Large sparse linear algebraic systems can be found in a variety of scientific and engineering fields, and many scientists strive to solve them in an efficient and robust manner. In this paper, we propose an interpretable neural solver, the…

Numerical Analysis · Mathematics 2022-10-11 Chen Cui , Kai Jiang , Yun Liu , Shi Shu

We study a class of functional problems reducible to computing $f^{(n)}(x)$ for inputs $n$ and $x$, where $f$ is a polynomial-time bijection. As we prove, the definition is robust against variations in the type of reduction used in its…

Computational Complexity · Computer Science 2024-02-14 David Eppstein

We introduce a new canonical form of lattices called the systematic normal form (SNF). We show that for every lattice there is an efficiently computable "nearby" SNF lattice, such that for any lattice one can solve lattice problems on its…

Computational Complexity · Computer Science 2016-04-27 Lior Eldar , Peter W. Shor

With the increasing demand for interpretability in machine learning, functional ANOVA decomposition has gained renewed attention as a principled tool for breaking down high-dimensional function into low-dimensional components that reveal…

Machine Learning · Statistics 2026-02-23 Seokhun Park , Choeun Kim , Jihu Lee , Yunseop Shin , Insung Kong , Yongdai Kim

Function approximation from input and output data pairs constitutes a fundamental problem in supervised learning. Deep neural networks are currently the most popular method for learning to mimic the input-output relationship of a general…

Machine Learning · Computer Science 2019-12-09 Nikos Kargas , Nicholas D. Sidiropoulos

In this paper, we identify a fragment of second-order logic with restricted quantification that is expressive enough to capture numerous static analysis problems (e.g. safety proving, bug finding, termination and non-termination proving,…

Logic in Computer Science · Computer Science 2015-09-01 Cristina David , Daniel Kroening , Matt Lewis

Whether the satisfiability of any formula F of propositional calculus can be determined in polynomial time is an open question. I propose a simple procedure based on some real world mechanisms to tackle this problem. The main result is the…

Logic in Computer Science · Computer Science 2010-01-20 Bernd R. Schuh

Analyzing a Feature Model (FM) and reasoning on the corresponding configuration space is a central task in Software Product Line (SPL) engineering. Problems such as deciding the satisfiability of the FM and eliminating inconsistent parts of…

Software Engineering · Computer Science 2023-02-15 Pierre Bourhis , Laurence Duchien , Jérémie Dusart , Emmanuel Lonca , Pierre Marquis , Clément Quinton

Perceptual sound matching (PSM) aims to find the input parameters to a synthesizer so as to best imitate an audio target. Deep learning for PSM optimizes a neural network to analyze and reconstruct prerecorded samples. In this context, our…

Sound · Computer Science 2024-05-07 Han Han , Vincent Lostanlen , Mathieu Lagrange

In this work, we consider the satisfiability problem in a logic that combines word equations over string variables denoting words of unbounded lengths, regular languages to which words belong and Presburger constraints on the length of…

Logic in Computer Science · Computer Science 2018-05-24 Quang Loc Le