Subset models for justification logic

Lehmann, Eveline; Studer, Thomas (July 2019). Subset models for justification logic. Lecture notes in computer science, 11541, pp. 433-449. Springer 10.1007/978-3-662-59533-6_26

[img]
Preview
Text
subsetmodelsWollic.pdf - Accepted Version
Available under License Publisher holds Copyright.

Download (364kB) | Preview
[img] Text
Lehmann-Studer2019_Chapter_SubsetModelsForJustificationLo.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (324kB) | Request a copy

We introduce a new semantics for justification logic based on subset relations. Instead of using the established and more symbolic interpretation of justifications, we model justifications as sets of possible worlds. We introduce a new justification logic that is sound and complete with respect to our semantics. Moreover, we present another variant of our semantics that corresponds to traditional justification logic. These types of models offer us a versatile tool to work with justifications, e.g. by extending them with a probability measure to capture uncertain justifications. Following this strategy we will show that they subsume Artemov’s approach to aggregating probabilistic evidence.

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

ISSN:

0302-9743

ISBN:

978-3-662-59533-6

Publisher:

Springer

Language:

English

Submitter:

Nenad Savic

Date Deposited:

21 Oct 2019 09:33

Last Modified:

10 Jun 2020 02:30

Publisher DOI:

10.1007/978-3-662-59533-6_26

BORIS DOI:

10.7892/boris.133989

URI:

https://boris.unibe.ch/id/eprint/133989

Actions (login required)

Edit item Edit item
Provide Feedback