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Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that appear in imprecise-probabilistic decision…

Artificial Intelligence · Computer Science 2019-05-22 Jasper De Bock , Gert de Cooman

Every countable language which conforms to classical logic is shown to have an extension which conforms to classical logic, and has a definitional theory of truth. That extension has a semantical theory of truth, if every sentence of the…

Logic · Mathematics 2020-02-04 Seppo Heikkilä

Argumentation is a non-monotonic process. This reflects the fact that argumentation involves uncertain information, and so new information can cause a change in the conclusions drawn. However, the base logic does not need to be…

Artificial Intelligence · Computer Science 2018-09-05 Anthony Hunter

We construct representation theory of Lie algebras with filtrations. In this framework a classification of irreducible representations is obtained and spectra of some reducible representations are found.

Representation Theory · Mathematics 2012-03-01 A. N. Panov

This chapter presents probability logic as a rationality framework for human reasoning under uncertainty. Selected formal-normative aspects of probability logic are discussed in the light of experimental evidence. Specifically, probability…

Artificial Intelligence · Computer Science 2019-10-16 Niki Pfeifer

The Turing machine, as it was presented by Turing himself, models the calculations done by a person. This means that we can compute whatever any Turing machine can compute, and therefore we are Turing complete. The question addressed here…

Artificial Intelligence · Computer Science 2016-09-05 Ramón Casares

In causal models, a given mechanism is assumed to be invariant to changes of other mechanisms. While this principle has been utilized for inference in settings where the causal variables are observed, theoretical insights when the variables…

Machine Learning · Statistics 2023-12-07 Simon Bing , Jonas Wahl , Urmi Ninad , Jakob Runge

Automated reasoning about uncertain knowledge has many applications. One difficulty when developing such systems is the lack of a completely satisfactory integration of logic and probability. We address this problem directly. Expressive…

Logic in Computer Science · Computer Science 2012-09-13 Marcus Hutter , John W. Lloyd , Kee Siong Ng , William T. B. Uther

We are concerned with the problem of introducing credibility type information into reasoning systems. The concept of credibility allows us to discount information provided by agents. An important characteristic of this kind of procedure is…

Artificial Intelligence · Computer Science 2013-04-05 Ronald R. Yager

It is standard to regard the intuitionistic restriction of a classical logic as increasing the expressivity of the logic because the classical logic can be adequately represented in the intuitionistic logic by double-negation, while the…

Logic in Computer Science · Computer Science 2010-06-17 Kaustuv Chaudhuri

It is generally believed (and for the most part is probably true) that Lie theory, in contrast to the characteristic zero case, is insufficient to tackle the representation theory of algebraic groups over prime characteristic fields.…

Representation Theory · Mathematics 2011-05-26 Michael Crumley

We address the problem of compiling defeasible theories to Datalog$^\neg$ programs. We prove the correctness of this compilation, for the defeasible logic $DL(\partial_{||})$, but the techniques we use apply to many other defeasible logics.…

Logic in Computer Science · Computer Science 2024-08-28 Michael J. Maher

We introduce a setting for learning possibilistic logic theories from defaults of the form "if alpha then typically beta". We first analyse this problem from the point of view of machine learning theory, determining the VC dimension of…

Artificial Intelligence · Computer Science 2016-04-19 Ondrej Kuzelka , Jesse Davis , Steven Schockaert

The standard approach to logic in the literature in philosophy and mathematics, which has also been adopted in computer science, is to define a language (the syntax), an appropriate class of models together with an interpretation of…

Artificial Intelligence · Computer Science 2009-09-25 Joseph Y. Halpern

Argumentation has proved a useful tool in defining formal semantics for assumption-based reasoning by viewing a proof as a process in which proponents and opponents attack each others arguments by undercuts (attack to an argument's premise)…

Logic in Computer Science · Computer Science 2007-05-23 Ralf Schweimeier , Michael Schroeder

First-Order Logic (FOL) is widely regarded as one of the most important foundations for knowledge representation. Nevertheless, in this paper, we argue that FOL has several critical issues for this purpose. Instead, we propose an…

Artificial Intelligence · Computer Science 2017-05-01 Yi Zhou

We provide a sound and complete proof system for an extension of Kleene's ternary logic to predicates. The concept of theory is extended with, for each function symbol, a formula that specifies when the function is defined. The notion of…

Logic · Mathematics 2023-03-28 Antti Valmari , Lauri Hella

In this paper, we consider the problem of learning a first-order theorem prover that uses a representation of beliefs in mathematical claims to construct proofs. The inspiration for doing so comes from the practices of human mathematicians…

Artificial Intelligence · Computer Science 2019-07-01 Daniel Huang

Many systems that exhibit nonmonotonic behavior have been described and studied already in the literature. The general notion of nonmonotonic reasoning, though, has almost always been described only negatively, by the property it does not…

Artificial Intelligence · Computer Science 2007-05-23 Sarit Kraus , Daniel Lehmann , Menachem Magidor

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
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