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Related papers: Probabilistic and Non-Monotonic Inference

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A number of writers(Joseph Halpern and Fahiem Bacchus among them) have offered semantics for formal languages in which inferences concerning probabilities can be made. Our concern is different. This paper provides a formalization of…

Artificial Intelligence · Computer Science 2013-03-25 Henry E. Kyburg

This note is concerned with a formal analysis of the problem of non-monotonic reasoning in intelligent systems, especially when the uncertainty is taken into account in a quantitative way. A firm connection between logic and probability is…

Artificial Intelligence · Computer Science 2013-04-05 Hung-Trung Nguyen

Nonmonotonic reasoning is a pattern of reasoning that allows an agent to make and retract (tentative) conclusions from inconclusive evidence. This paper gives a possible-worlds interpretation of the nonmonotonic reasoning problem based on…

Artificial Intelligence · Computer Science 2013-04-10 Carl Kadie

Probability theory, epistemically interpreted, provides an excellent, if not the best available account of inductive reasoning. This is so because there are general and definite rules for the change of subjective probabilities through…

Artificial Intelligence · Computer Science 2013-04-10 Wolfgang Spohn

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

Attempts to replicate probabilistic reasoning in expert systems have typically overlooked a critical ingredient of that process. Probabilistic analysis typically requires extensive judgments regarding interdependencies among hypotheses and…

Artificial Intelligence · Computer Science 2013-04-15 Marvin S. Cohen

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

Considerable attention has been given to the problem of non-monotonic reasoning in a belief function framework. Earlier work (M. Ginsberg) proposed solutions introducing meta-rules which recognized conditional independencies in a…

Artificial Intelligence · Computer Science 2013-04-05 Mary McLeish

The idea of fully accepting statements when the evidence has rendered them probable enough faces a number of difficulties. We leave the interpretation of probability largely open, but attempt to suggest a contextual approach to full belief.…

Artificial Intelligence · Computer Science 2013-02-08 Henry E. Kyburg

In many situations humans have to reason with inconsistent knowledge. These inconsistencies may occur due to not fully reliable sources of information. In order to reason with inconsistent knowledge, it is not possible to view a set of…

Artificial Intelligence · Computer Science 2024-12-16 Nico Roos

In [12], Nilsson proposed the probabilistic logic in which the truth values of logical propositions are probability values between 0 and 1. It is applicable to any logical system for which the consistency of a finite set of propositions can…

Artificial Intelligence · Computer Science 2013-04-12 Su-shing Chen

We present a computable algorithm that assigns probabilities to every logical statement in a given formal language, and refines those probabilities over time. For instance, if the language is Peano arithmetic, it assigns probabilities to…

Artificial Intelligence · Computer Science 2020-12-09 Scott Garrabrant , Tsvi Benson-Tilsen , Andrew Critch , Nate Soares , Jessica Taylor

We propose an inequality paradigm for probabilistic reasoning based on a logic of upper and lower bounds on conditional probabilities. We investigate a family of probabilistic logics, generalizing the work of Nilsson [14]. We develop a…

Artificial Intelligence · Computer Science 2013-04-15 Benjamin N. Grosof

In this paper, we provide more evidence for the contention that logical consequence should be understood in normative terms. Hartry Field and John MacFarlane covered the classical case. We extend their work, examining what it means for an…

Logic in Computer Science · Computer Science 2014-02-20 Julio Lemos

We start by defining an approach to non-monotonic probabilistic reasoning in terms of non-monotonic categorical (true-false) reasoning. We identify a type of non-monotonic probabilistic reasoning, akin to default inheritance, that is…

Artificial Intelligence · Computer Science 2013-04-12 Benjamin N. Grosof

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

The problem of induction has persisted since Hume exposed the logical gap between repeated observation and universal inference. Traditional attempts to resolve it have oscillated between two extremes: the probabilistic optimism of Laplace…

Other Statistics · Statistics 2025-11-06 Tommaso Costa

Tarski gave a general semantics for deductive reasoning: a formula a may be deduced from a set A of formulas iff a holds in all models in which each of the elements of A holds. A more liberal semantics has been considered: a formula a may…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

The role of probability appears unchallenged as the key measure of uncertainty, used among other things for practical induction in the empirical sciences. Yet, Popper was emphatic in his rejection of inductive probability and of the logical…

Other Statistics · Statistics 2021-08-04 Youngjo Lee , Yudi Pawitan

Stereotypical reasoning assumes that the situation at hand is one of a kind and that it enjoys the properties generally associated with that kind of situation. It is one of the most basic forms of nonmonotonic reasoning. A formal model for…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann
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