Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Probabilistic description logics for subjective uncertainty

Gutierrez Basulto, Victor, Jung, Jean Christoph, Lutz, Carsten and Schroeder, Lutz 2017. Probabilistic description logics for subjective uncertainty. Journal of Artificial Intelligence Research 58 , pp. 1-66. 10.1613/jair.5222

[img]
Preview
PDF - Published Version
Download (577kB) | Preview

Abstract

We propose a family of probabilistic description logics (DLs) that are derived in a principled way from Halpern's probabilistic first-order logic. The resulting probabilistic DLs have a two-dimensional semantics similar to temporal DLs and are well-suited for representing subjective probabilities. We carry out a detailed study of reasoning in the new family of logics, concentrating on probabilistic extensions of the DLs ALC and EL, and showing that the complexity ranges from PTime via ExpTime and 2ExpTime to undecidable.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Publisher: AI Access Foundation
ISSN: 1076-9757
Date of First Compliant Deposit: 4 June 2018
Date of Acceptance: 3 January 2017
Last Modified: 16 Jul 2019 13:45
URI: http://orca.cf.ac.uk/id/eprint/111926

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics