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Defeasible logic is a rule-based nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts…

Artificial Intelligence · Computer Science 2009-09-29 Michael J. Maher

Predictive models are being increasingly used to support consequential decision making at the individual level in contexts such as pretrial bail and loan approval. As a result, there is increasing social and legal pressure to provide…

Machine Learning · Computer Science 2020-03-02 Amir-Hossein Karimi , Gilles Barthe , Borja Balle , Isabel Valera

Beginning with a simple semantics for propositions, based on counting observations, it is shown that probabilistic and fuzzy logic correspond to two different heuristic assumptions regarding the combination of propositions whose evidence…

Artificial Intelligence · Computer Science 2020-09-29 Ben Goertzel

LogicWeb has traditionally lacked devices for dealing with intractable queries. We address this limitation by adopting length-bounded inference, a form of approximate reasoning. A length-bounded inference is of the form $prov(P,G,n)$ which…

Logic in Computer Science · Computer Science 2017-10-19 Keehang Kwon , Daeseong Kang

In solving a query, the SLD proof procedure for definite programs sometimes searches an infinite space for a non existing solution. For example, querying a planner for an unreachable goal state. Such programs motivate the development of…

Logic in Computer Science · Computer Science 2007-05-23 Maurice Bruynooghe , Henk Vandecasteele , D. Andre de Waal , Marc Denecker

The provability logic of a theory T is the set of modal formulas, which under any arithmetical realization are provable in T . We slightly modify this notion by requiring the arithmetical realizations to come from a specified set $\Gamma$.…

Logic · Mathematics 2020-06-19 Thomas F. Icard , Joost J. Joosten

Tackling Natural Language Inference with a logic-based method is becoming less and less common. While this might have been counterintuitive several decades ago, nowadays it seems pretty obvious. The main reasons for such a conception are…

Computation and Language · Computer Science 2020-12-02 Lasha Abzianidze

Induction in saturation-based first-order theorem proving is a new exciting direction in the automation of inductive reasoning. In this paper we survey our work on integrating induction directly into the saturation-based proof search…

Logic in Computer Science · Computer Science 2024-03-01 Márton Hajdu , Petra Hozzová , Laura Kovács , Giles Reger , Andrei Voronkov

Counterfactual learning is a natural scenario to improve web-based machine translation services by offline learning from feedback logged during user interactions. In order to avoid the risk of showing inferior translations to users, in such…

Machine Learning · Statistics 2017-12-15 Carolin Lawrence , Pratik Gajane , Stefan Riezler

This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argumentative-consequence relation taking into account the existence of consistent arguments in favor of a conclusion and the…

Artificial Intelligence · Computer Science 2013-03-08 Salem Benferhat , Didier Dubois , Henri Prade

The study of machine learning-based logical query answering enables reasoning with large-scale and incomplete knowledge graphs. This paper advances this area of research by addressing the uncertainty inherent in knowledge. While the…

Artificial Intelligence · Computer Science 2025-05-21 Weizhi Fei , Zihao Wang , Hang Yin , Yang Duan , Yangqiu Song

Inference amortization methods share information across multiple posterior-inference problems, allowing each to be carried out more efficiently. Generally, they require the inversion of the dependency structure in the generative model, as…

Machine Learning · Statistics 2018-11-30 Stefan Webb , Adam Golinski , Robert Zinkov , N. Siddharth , Tom Rainforth , Yee Whye Teh , Frank Wood

Doubly intractable problems occur when both the likelihood and the posterior are available only in unnormalised form, with computationally intractable normalisation constants. Bayesian inference then typically requires direct approximation…

This paper explores goal-directed proof search in first-order multi-modal logic. The key issue is to design a proof system that respects the modularity and locality of assumptions of many modal logics. By forcing ambiguities to be…

Logic in Computer Science · Computer Science 2007-05-23 Matthew Stone

Incomputability results in Formal Logic and the Theory of Computation (i.e., incompleteness and undecidability) have deep implications for the foundations of mathematics and computer science. Likewise, Social Choice Theory, a branch of…

Logic · Mathematics 2025-11-11 Ori Livson , Mikhail Prokopenko

Many representation schemes combining first-order logic and probability have been proposed in recent years. Progress in unifying logical and probabilistic inference has been slower. Existing methods are mainly variants of lifted variable…

Artificial Intelligence · Computer Science 2012-02-20 Vibhav Gogate , Pedro Domingos

The goal of a scientific investigation is to find answers to specific questions. In geosciences this is typically achieved by solving an inference or inverse problem and interpreting the solution. However, the answer obtained is often…

Geophysics · Physics 2022-01-05 Xin Zhang , Andrew Curtis

We consider the problem of exact probabilistic inference for Union of Conjunctive Queries (UCQs) on tuple-independent databases. For this problem, two approaches currently coexist. In the extensional method, query evaluation is performed by…

Databases · Computer Science 2021-04-29 Mikaël Monet

I deal with two approaches to proof-theoretic semantics: one based on argument structures and justifications, which I call reducibility semantics, and one based on consequence among (sets of) formulas over atomic bases, called base…

Logic · Mathematics 2025-11-11 Antonio Piccolomini d'Aragona

We study implicational formulas in the context of proof complexity of intuitionistic propositional logic (IPC). On the one hand, we give an efficient transformation of tautologies to implicational tautologies that preserves the lengths of…

Logic in Computer Science · Computer Science 2016-10-27 Emil Jeřábek