Belief Expansion in Subset Models

Lehmann, Eveline; Studer, Thomas (January 2020). Belief Expansion in Subset Models. In: Artemov, Sergei; Nerode, Anil (eds.) Logical Foundations of Computer Science LFCS 2020. Lecture Notes in Computer Science: Vol. 11972 (pp. 85-97). Springer 10.1007/978-3-030-36755-8_6

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Subset models provide a new semantics for justifcation logic.The main idea of subset models is that evidence terms are interpreted assets of possible worlds. A term then justifies a formula if that formula istrue in each world of the interpretation of the term.In this paper, we introduce a belief expansion operator for subset mod-els. We study the main properties of the resulting logic as well as thedifferences to a previous (symbolic) approach to belief expansion in jus-tification logic.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF) > Logic and Theory Group (LTG)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Lehmann, Eveline and Studer, Thomas

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISBN:

978-3-030-36754-1

Series:

Lecture Notes in Computer Science

Publisher:

Springer

Language:

English

Submitter:

Atefeh Rohani

Date Deposited:

02 Sep 2020 09:23

Last Modified:

02 Sep 2020 09:23

Publisher DOI:

10.1007/978-3-030-36755-8_6

BORIS DOI:

10.7892/boris.146175

URI:

https://boris.unibe.ch/id/eprint/146175

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