Multi-Attribute Decision Making using Weighted Description Logics

Preview

PDF
AcarPRUV14.pdf - Published
Download (355kB)

URL:	https://madoc.bib.uni-mannheim.de/36790
Additional URL:	http://ceur-ws.org/Vol-1205/00010001.pdf
URN:	urn:nbn:de:bsz:180-madoc-367909
Document Type:	Conference or workshop publication
Year of publication:	2014
Book title:	PRUV 2014 : Proceedings of the First Workshop on Logics for Reasoning about Preferences, Uncertainty, and Vagueness co-located with 7th International Joint Conference on Automated Reasoning (IJCAR 2014) Vienna, Austria, July 23-24, 2014
The title of a journal, publication series:	CEUR Workshop Proceedings
Volume:	1205
Page range:	1-14
Date of the conference:	23-24 July, 2014
Publisher:	Lukasiewicz, Thomas
Place of publication:	Aachen, Germany
Publishing house:	RWTH Aachen
ISSN:	1613-0073
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject:	004 Computer science, internet 330 Economics
Keywords (English):	Multi-Criteria Decision Making , Semantic Web , Description Logics , Multi-Attribute Decision Making , Utility Theory
Abstract:	We introduce a framework based on Description Logics, which can be used to encode and solve decision problems in terms of combining inference services in DL and utility theory to represent preferences of the agent. The novelty of the approach is that we consider ABoxes as alternatives and weighted concept and role assertions as preferences in terms of possible outcomes. We discuss a relevant use case to show the benefits of the approach from the decision theory point of view.
Additional information:	http://publications.wim.uni-mannheim.de/informatik/lski/AcarPRUV14.pdf