Correctness criteria of some algorithms for uncertain reasoning using incidence calculus
type: Item
instance of: scholarly article
title: Correctness criteria of some algorithms for uncertain reasoning using incidence calculus
zbMATH Open document ID: 0642.68178
DOI: 10.1007/BF02432147
author: Alan Bundy
published in: Journal of Automated Reasoning
publication date: 1986-01-01T00:00:00Z
review text: Incidence calculus is a technique for associating uncertainty values with logical sentences. These uncertainty values are called incidences and they are sets of points, which may be thought of as representing equivalence classes of situations, Tarskian models, or possible worlds. Incidence calculus was originally introduced by the author [(*)\ ibid. 1, 263-283 (1985; Zbl 0615.68067)]. Incidence calculus was designed to overcome various inherent problems with purely numeric mechanisms for uncertain reasoning. In particular, incidences can represent the dependence between sentences, which numbers cannot, and hence incidence calculus can provide genuine, probabilistic reasoning. In this paper we prove soundness and completeness results for some algorithms introduced in (*) and hence satisfy some of the correctness criteria for incidence calculus. These algorithms can be used for probabilistic reasoning and to check the consistency of the subjective probabilities of sentences.
Mathematics Subject Classification ID: 68T99
Mathematics Subject Classification ID: 68T20
Mathematics Subject Classification ID: 03B48
zbMATH DE Number: 4047206
zbMATH Keywords: inference
zbMATH Keywords: expert systems
zbMATH Keywords: probabilistic logic with truth functional connectives
zbMATH Keywords: uncertainty
zbMATH Keywords: incidence calculus
zbMATH Keywords: probabilistic reasoning
MaRDI profile type: Publication
cites work: Incidence calculus: A mechanism for probabilistic reasoning
full work available at URL: https://doi.org/10.1007/bf02432147
OpenAlex ID: W2057002094
description: scientific article; zbMATH DE number 4047206