Title
Enrichment of Qualitative Beliefs for Reasoning under Uncertainty
Abstract
This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels. In this work, two possible enrichments (quantitative and/or qualitative) of linguistic labels are considered and operators (addition, multiplication, division, etc) for dealing with them are proposed and explained. We denote them qe-operators, qe standing for "qualitative-enriched" operators. These operators can be seen as a direct extension of the classical qualitative operators (q- operators) proposed in the Dezert-Smarandache theory of plausible and paradoxist reasoning (DSmT). q-operators are also justified in details in this paper. The quantitative enrichment of linguistic label is a numerical supporting degree in [0,infin), while the qualitative enrichment takes its values in a finite ordered set of linguistic values. Quantitative enrichment is less precise than qualitative enrichment, but it is expected more close with what human experts can easily provide when expressing linguistic labels with supporting degrees. Two simple examples are given to show how the fusion of qualitative-enriched belief assignments can be done, and a simulation application is given to show its advantage in rough navigation map building of mobile robot.
Year
DOI
Venue
2007
10.1109/ICIF.2007.4408179
Quebec, Que.
Keywords
DocType
Volume
natural language
Conference
abs/0709.1701
Issue
ISBN
Citations 
null
978-0-662-45804-3
1
PageRank 
References 
Authors
0.43
0
4
Name
Order
Citations
PageRank
Xinde Li15011.00
Xinhan Huang211419.04
Florentin Smarandache3728104.92
Jean Dezert477761.59