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Over the last couple of decades, there has been a considerable effort devoted to the problem of updating logic programs under the stable model semantics (a.k.a. answer-set programs) or, in other words, the problem of characterising the…

Artificial Intelligence · Computer Science 2022-02-22 João Leite , Martin Slota

Game semantics describe the interactive behavior of proofs by interpreting formulas as games on which proofs induce strategies. Such a semantics is introduced here for capturing dependencies induced by quantifications in first-order…

Logic in Computer Science · Computer Science 2009-08-28 Samuel Mimram

We conceptualize explainability in terms of logic and formula size, giving a number of related definitions of explainability in a very general setting. Our main interest is the so-called special explanation problem which aims to explain the…

Artificial Intelligence · Computer Science 2022-10-26 Reijo Jaakkola , Tomi Janhunen , Antti Kuusisto , Masood Feyzbakhsh Rankooh , Miikka Vilander

The design and implementation of precise static analyzers for significant fragments of modern imperative languages like C, C++, Java and Python is a challenging problem. In this paper, we consider a core imperative language that has several…

Programming Languages · Computer Science 2007-06-28 Roberto Bagnara , Patricia M. Hill , Andrea Pescetti , Enea Zaffanella

Recently Ferraris, Lee and Lifschitz proposed a new definition of stable models that does not refer to grounding, which applies to the syntax of arbitrary first-order sentences. We show its relation to the idea of loop formulas with…

Artificial Intelligence · Computer Science 2023-07-21 Joohyung Lee , Yunsong Meng

As a contribution to the challenge of building game-playing AI systems, we develop and analyse a formal language for representing and reasoning about strategies. Our logical language builds on the existing general Game Description Language…

Artificial Intelligence · Computer Science 2014-07-22 Dongmo Zhang , Michael Thielsher

Answer Set Programming (ASP) emerged in the late 1990ies as a paradigm for Knowledge Representation and Reasoning. The attractiveness of ASP builds on an expressive high-level modeling language along with the availability of powerful…

Artificial Intelligence · Computer Science 2021-09-20 Mario Alviano , Wolfgang Faber , Martin Gebser

Abstract argumentation frameworks (AFs) provide a formal setting to analyze many forms of reasoning with conflicting information. While the expressiveness of general infinite AFs make them a tempting tool for modeling many kinds of…

Artificial Intelligence · Computer Science 2025-08-26 Uri Andrews , Luca San Mauro

This thesis develops the translation between category theory and computational linguistics as a foundation for natural language processing. The three chapters deal with syntax, semantics and pragmatics. First, string diagrams provide a…

Computation and Language · Computer Science 2022-12-14 Giovanni de Felice

We describe two systems currently being developed that use large language models for the automatized correction of (i) exercises in translating back and forth between natural language and the languages of propositional logic and first-order…

Computation and Language · Computer Science 2024-04-11 Merlin Carl

We propose a computational modeling framework for inducing combinatory categorial grammars from arbitrary behavioral data. This framework provides the analyst fine-grained control over the assumptions that the induced grammar should conform…

Computation and Language · Computer Science 2020-10-19 Gene Louis Kim , Aaron Steven White

This paper shows that the semantics of programs with aggregates implemented by the solvers clingo and dlv can be characterized as extended First-Order formulas with intensional functions in the logic of Here-and-There. Furthermore, this…

Artificial Intelligence · Computer Science 2024-12-17 Jorge Fandinno , Zachary Hansen

Answer set programming is a prominent declarative programming paradigm used in formulating combinatorial search problems and implementing different knowledge representation formalisms. Frequently, several related and yet substantially…

Artificial Intelligence · Computer Science 2023-03-01 Yuliya Lierler

We develop operators for construction of proposals in probabilistic programs, which we refer to as inference combinators. Inference combinators define a grammar over importance samplers that compose primitive operations such as application…

Machine Learning · Statistics 2021-06-18 Sam Stites , Heiko Zimmermann , Hao Wu , Eli Sennesh , Jan-Willem van de Meent

Distributional compositional (DisCo) models are functors that compute the meaning of a sentence from the meaning of its words. We show that DisCo models in the category of sets and relations correspond precisely to relational databases. As…

Computation and Language · Computer Science 2020-09-16 Giovanni de Felice , Konstantinos Meichanetzidis , Alexis Toumi

We present xclingo, a tool for generating explanations from ASP programs annotated with text and labels. These annotations allow tracing the application of rules or the atoms derived by them. The input of xclingo is a markup language…

Artificial Intelligence · Computer Science 2020-09-23 Pedro Cabalar , Jorge Fandinno , Brais Muñiz

We analyse the expressiveness of the two-valued semantics of abstract argumentation frameworks, normal logic programs and abstract dialectical frameworks. By expressiveness we mean the ability to encode a desired set of two-valued…

Artificial Intelligence · Computer Science 2014-05-06 Hannes Strass

Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there is constraint logic programming which computes a solution as an answer substitution to a query containing the…

Artificial Intelligence · Computer Science 2007-05-23 Nikolay Pelov , Emmanuel De Mot , Marc Denecker

Conventional spoken language understanding systems consist of two main components: an automatic speech recognition module that converts audio to a transcript, and a natural language understanding module that transforms the resulting text…

Audio and Speech Processing · Electrical Eng. & Systems 2021-02-16 Parisa Haghani , Arun Narayanan , Michiel Bacchiani , Galen Chuang , Neeraj Gaur , Pedro Moreno , Rohit Prabhavalkar , Zhongdi Qu , Austin Waters

Generalizations of linear numeration systems in which the set of natural numbers is recognizable by finite automata are obtained by describing an arbitrary infinite regular language following the lexicographic ordering. For these systems of…

Other Computer Science · Computer Science 2007-05-23 Pierre B. A. Lecomte , Michel Rigo
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