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Compilers use control flow graph (CFG) representations of low-level programs because they are suited to program analysis and optimizations. However, formalizing the behavior and metatheory of CFG programs is non-trivial: CFG programs don't…

Programming Languages · Computer Science 2018-05-16 Dmitri Garbuzov , William Mansky , Christine Rizkallah , Steve Zdancewic

Bigraphs are an emerging modeling formalism for structures in ubiquitous computing. Besides an algebraic notation, which can be adopted to provide an algebraic syntax for bigraphs, the bigraphical theory introduces a visual concrete syntax…

Software Engineering · Computer Science 2016-12-07 Timo Kehrer , Christos Tsigkanos , Carlo Ghezzi

Detection and elimination of redundant clauses from propositional formulas in Conjunctive Normal Form (CNF) is a fundamental problem with numerous application domains, including AI, and has been the subject of extensive research. Moreover,…

Logic in Computer Science · Computer Science 2012-07-11 Anton Belov , Joao Marques-Silva

Matrix syntax is a formal model of syntactic relations in language. The purpose of this paper is to explain its mathematical foundations, for an audience with some formal background. We make an axiomatic presentation, motivating each axiom…

Computation and Language · Computer Science 2019-03-12 Roman Orus , Roger Martin , Juan Uriagereka

Syntactic NL or succinctly SNL was first introduced in 2017, analogously to SNP, as a ``syntactically''-defined natural subclass of NL (nondeterministic logarithmic-space complexity class) using a restricted form of logical sentences,…

Computational Complexity · Computer Science 2025-11-07 Tomoyuki Yamakami

We describe a machine learning method for predicting the value of a real-valued function, given the values of multiple input variables. The method induces solutions from samples in the form of ordered disjunctive normal form (DNF) decision…

Artificial Intelligence · Computer Science 2014-11-17 S. M. Weiss , N. Indurkhya

We introduce Nominal Matching Logic (NML) as an extension of Matching Logic with names and binding following the Gabbay-Pitts nominal approach. Matching logic is the foundation of the $\mathbb{K}$ framework, used to specify programming…

Logic in Computer Science · Computer Science 2022-07-29 James Cheney , Maribel Fernández

This paper proposes algorithms for learning two-level Boolean rules in Conjunctive Normal Form (CNF, i.e. AND-of-ORs) or Disjunctive Normal Form (DNF, i.e. OR-of-ANDs) as a type of human-interpretable classification model, aiming for a…

Machine Learning · Computer Science 2015-11-24 Guolong Su , Dennis Wei , Kush R. Varshney , Dmitry M. Malioutov

The logic of hybrid MKNF (minimal knowledge and negation as failure) is a powerful knowledge representation language that elegantly pairs ASP (answer set programming) with ontologies. Disjunctive rules are a desirable extension to normal…

Artificial Intelligence · Computer Science 2022-08-08 Spencer Killen , Jia-Huai You

The functorial structure of type constructors is the foundation for many definition and proof principles in higher-order logic (HOL). For example, inductive and coinductive datatypes can be built modularly from bounded natural functors…

Logic in Computer Science · Computer Science 2023-06-22 Basil Fürer , Andreas Lochbihler , Joshua Schneider , Dmitriy Traytel

Bilattices provide an algebraic tool with which to model simultaneously knowledge and truth. They were introduced by Belnap in 1977 in a paper entitled \emph{How a computer should think}. Belnap argued that instead of using a logic with two…

Logic · Mathematics 2019-05-07 Andrew Craig , Brian A. Davey , Miroslav Haviar

We propose a new algorithm for compiling Bayesian network classifier (BNC) into class formulas. Class formulas are logical formulas that represent a classifier's input-output behavior, and are crucial in the recent line of work that uses…

Artificial Intelligence · Computer Science 2026-03-17 Yaofang Zhang , Adnan Darwiche

Here, in a series of articles, we show methods for calculating propositional statements using algebraic polynomials as symbols for the connectives, which are named operators. These polynomials originate from the transformation between the…

Logic · Mathematics 2026-02-09 Pelle Brooke Borgeke

While the deployment of neural networks, yielding impressive results, becomes more prevalent in various applications, their interpretability and understanding remain a critical challenge. Network inversion, a technique that aims to…

Machine Learning · Computer Science 2024-02-20 Pirzada Suhail , Supratik Chakraborty , Amit Sethi

Approximation Fixpoint Theory (AFT) is a powerful theory covering various semantics of non-monotonic reasoning formalisms in knowledge representation such as Logic Programming and Answer Set Programming. Many semantics of such non-monotonic…

Artificial Intelligence · Computer Science 2025-06-23 Linde Vanbesien , Bart Bogaerts , Marc Denecker

Mathematical notations around the world are diverse. Not as much as requiring computing machines' makers to adapt to each culture, but as much as to disorient a person landing on a web-page with a text in mathematics. In order to understand…

Digital Libraries · Computer Science 2010-04-30 Paul Libbrecht

Linear algebra computations are foundational for neural networks and machine learning, often handled through arrays. While many functional programming languages feature lists and recursion, arrays in linear algebra demand constant-time…

Programming Languages · Computer Science 2024-05-29 David Richter , Timon Böhler , Pascal Weisenburger , Mira Mezini

We present the formalization of a theory of syntax with bindings that has been developed and refined over the last decade to support several large formalization efforts. Terms are defined for an arbitrary number of constructors of varying…

Logic in Computer Science · Computer Science 2017-07-04 Lorenzo Gheri , Andrei Popescu

This presentation discusses a new, modular, more mature architecture for the Information Flow Framework (IFF). The IFF uses institution theory as a foundation for the semantic integration of ontologies. It represents metalogic, and as such…

Digital Libraries · Computer Science 2011-09-06 Robert E. Kent

Graph neural networks (GNNs) are frequently used for knowledge graph completion. Their black-box nature has motivated work that uses sound logical rules to explain predictions and characterise their expressivity. However, despite the…

Machine Learning · Computer Science 2025-11-18 Matthew Morris , Ian Horrocks