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Intercausal reasoning is a common inference pattern involving probabilistic dependence of causes of an observed common effect. The sign of this dependence is captured by a qualitative property called product synergy. The current definition…

Artificial Intelligence · Computer Science 2013-03-08 Marek J. Druzdzel , Max Henrion

A knowledge system S describing a part of real world does in general not contain complete information. Reasoning with incomplete information is prone to errors since any belief derived from S may be false in the present state of the world.…

Artificial Intelligence · Computer Science 2011-05-20 Eliezer L. Lozinskii

Abductive reasoning aims to find plausible explanations for an event. This style of reasoning is critical for commonsense tasks where there are often multiple plausible explanations. Existing approaches for abductive reasoning in natural…

Computation and Language · Computer Science 2023-05-25 Wenting Zhao , Justin T. Chiu , Claire Cardie , Alexander M. Rush

Justification theory is an abstract unifying formalism that captures semantics of various non-monotonic logics. One intriguing problem that has received significant attention is the consistency problem: under which conditions are…

Artificial Intelligence · Computer Science 2022-08-08 Simon Marynissen , Bart Bogaerts

Predicting the future is an important component of decision making. In most situations, however, there is not enough information to make accurate predictions. In this paper, we develop a theory of causal reasoning for predictive inference…

Artificial Intelligence · Computer Science 2013-04-10 Thomas L. Dean , Keiji Kanazawa

A type theory is presented that combines (intuitionistic) linear types with type dependency, thus properly generalising both intuitionistic dependent type theory and full linear logic. A syntax and complete categorical semantics are…

Logic in Computer Science · Computer Science 2026-05-07 Matthijs Vákár

We argue for a compositional semantics grounded in a strongly typed ontology that reflects our commonsense view of the world and the way we talk about it. Assuming such a structure we show that the semantics of various natural language…

Artificial Intelligence · Computer Science 2007-05-23 Walid S. Saba

Our understanding about things is conceptual. By stating that we reason about objects, it is in fact not the objects but concepts referring to them that we manipulate. Now, so long just as we acknowledge infinitely extending notions such as…

Artificial Intelligence · Computer Science 2015-04-21 Ryuta Arisaka

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

A type theory is presented that combines (intuitionistic) linear types with type dependency, thus properly generalising both intuitionistic dependent type theory and full linear logic. A syntax and complete categorical semantics are…

Logic in Computer Science · Computer Science 2026-05-07 Matthijs Vákár

The propositional logic is generalized on the real numbers field. the logical function with all properties of the classical probability function is obtained. The logical analog of the Bernoulli independent tests scheme is constructed. The…

General Mathematics · Mathematics 2007-05-23 G. A. Quznetsov

Dialectical logic is the logic of dialectical processes. The goal of dialectical logic is to introduce dynamic notions into logical computational systems. The fundamental notions of proposition and truth-value in standard logic are subsumed…

Logic in Computer Science · Computer Science 2011-09-13 Robert E. Kent

Underlying the theory of inferences, a primary task of logic is language analysis. Such a task can be understood as depending on a general theory of representation, taking as a starting point the idea that some entities (`` representations…

Logic in Computer Science · Computer Science 2023-07-21 Arnaud Plagnol

Argumentation is the process of constructing arguments about propositions, and the assignment of statements of confidence to those propositions based on the nature and relative strength of their supporting arguments. The process is modelled…

Artificial Intelligence · Computer Science 2013-03-08 John Fox , Paul J. Krause , Morten Elvang-Gøransson

We investigate properties of ABA+, a formalism that extends the well studied structured argumentation formalism Assumption-Based Argumentation (ABA) with a preference handling mechanism. In particular, we establish desirable properties that…

Artificial Intelligence · Computer Science 2017-11-07 Kristijonas Cyras , Francesca Toni

Common knowledge/belief in rationality is the traditional standard assumption in analysing interaction among agents. This paper proposes a graph-based language for capturing significantly more complicated structures of higher-order beliefs…

Artificial Intelligence · Computer Science 2024-12-13 Qi Shi , Pavel Naumov

This paper considers the complexity and properties of KLM-style preferential reasoning in the setting of propositional logic with team semantics and dependence atoms, also known as propositional dependence logic. Preferential team-based…

Artificial Intelligence · Computer Science 2025-05-14 Kai Sauerwald , Arne Meier , Juha Kontinen

Language models (LMs) are said to be exhibiting reasoning, but what does this entail? We assess definitions of reasoning and how key papers in the field of natural language processing (NLP) use the notion and argue that the definitions…

Computation and Language · Computer Science 2025-11-18 Bertram Højer

Minimizing the relative inertia of a statistical group with respect to the inertia of the overall sample defines an unique point, the in-focus, which constitutes a context-dependent measure of typical group tendency, biased in comparison to…

Applications · Statistics 2010-04-06 François Bavaud

The systematic biases seen in people's probability judgments are typically taken as evidence that people do not reason about probability using the rules of probability theory, but instead use heuristics which sometimes yield reasonable…

Data Analysis, Statistics and Probability · Physics 2014-05-01 Fintan Costello , Paul Watts