Probabilistic belief revision via imaging

Kinzang Chhogyal*, Abhaya Nayak, Rolf Schwitter, Abdul Sattar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

6 Citations (Scopus)

Abstract

While Bayesian conditioning fits in nicely with probabilistic belief expansion, its use is problematic in the context of non-trivial belief revision. Lewis’ use of imaging based on closeness between possible worlds offers a way to overcome this limitation in the context of belief update (in a dynamic environment). In this paper, we explore the use of imaging as a means to construct probabilistic belief revision. Specifically, we present explicit constructions of three candidates strategies, dubbed Naive, Gullible and Cunning, that are based on imaging, and investigate their properties.

Original languageEnglish
Title of host publicationPRICAI 2014: Trends in Artificial Intelligence
Subtitle of host publication13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings
EditorsDuc-Nghia Pham, Seong-Bae Park
Place of PublicationCham
PublisherSpringer, Springer Nature
Pages694-707
Number of pages14
Volume8862
Edition1st
ISBN (Electronic)9783319135601
ISBN (Print)9783319135595
DOIs
Publication statusPublished - 2014
Event13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014 - Gold Coast, QLD, Australia
Duration: 1 Dec 20145 Dec 2014

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
ISSN (Print)0302-9743

Conference

Conference13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014
CountryAustralia
CityGold Coast, QLD
Period1/12/145/12/14

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Chhogyal, K., Nayak, A., Schwitter, R., & Sattar, A. (2014). Probabilistic belief revision via imaging. In D-N. Pham, & S-B. Park (Eds.), PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings (1st ed., Vol. 8862, pp. 694-707). (Lecture Notes in Computer Science). Cham: Springer, Springer Nature. https://doi.org/10.1007/978-3-319-13560-1_55