Temporal belief-change

κ-functions approach

Armin Hezart*, Abhaya Nayak, Mehmet A. Orgun

*Corresponding author for this work

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

Abstract

Current belief change literature is largely confined to atemporal belief change - the temporal element of beliefs is not explicitly recognized or represented. In this paper, we present a temporal belief change framework that is based on applying Spohn's theory of ranking functions to certain temporal semantic objects that we call 'histories'. The resulting framework allows us to address a class of problems for which Jeffery's general conditionalization, and Spohn's cardinality of the ranks, as well as the dependencies between beliefs play a central role. This allows us to lend further support to the argument that the application of the AGM theory is not necessarily limited to a static world. We also present an interpretation of belief update in the context of ranking-functions that has been missing in the literature.

Original languageEnglish
Title of host publicationAI 2010: Advances in Artificial Intelligence - 23rd Australasian Joint Conference, Proceedings
EditorsJiuyong Li
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Pages11-21
Number of pages11
Volume6464 LNAI
ISBN (Print)3642174310, 9783642174315
DOIs
Publication statusPublished - 2010
Event23rd Australasian Joint Conference on Artificial Intelligence, AI 2010 - Adelaide, SA, Australia
Duration: 7 Dec 201010 Dec 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6464 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other23rd Australasian Joint Conference on Artificial Intelligence, AI 2010
CountryAustralia
CityAdelaide, SA
Period7/12/1010/12/10

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Hezart, A., Nayak, A., & Orgun, M. A. (2010). Temporal belief-change: κ-functions approach. In J. Li (Ed.), AI 2010: Advances in Artificial Intelligence - 23rd Australasian Joint Conference, Proceedings (Vol. 6464 LNAI, pp. 11-21). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6464 LNAI). Berlin; Heidelberg: Springer, Springer Nature. https://doi.org/10.1007/978-3-642-17432-2_2