Inconsistency and semantic unification

Baldwin et al. in their work Fril—fuzzy and evidential reasoning [Artificial Intelligence, Research Studies Press Ltd, Taunton, UK, 1995] present a semantic unification function for mass assignment logic. Its purpose is to evaluate the truth that a claim X is supported by evidence Y. This paper expo...

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Bibliographic Details
Published in:Fuzzy sets and systems 2006-09, Vol.157 (18), p.2513-2539
Main Authors: Patching, R.S., Hinde, C.J., McCoy, S.A.
Format: Article
Language:English
Subjects:
Applied sciences
Circuit properties
Computer science
control theory
systems
Control theory. Systems
Digital circuits
Electric, optical and optoelectronic circuits
Electronic circuits
Electronics
Exact sciences and technology
Inconsistency
Information, signal and communications theory
Mass assignment
Mathematical methods
Miscellaneous
Non-classical logics
Semantic unification
System theory
Telecommunications and information theory
Theoretical computing
Truth valuation
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Summary:Baldwin et al. in their work Fril—fuzzy and evidential reasoning [Artificial Intelligence, Research Studies Press Ltd, Taunton, UK, 1995] present a semantic unification function for mass assignment logic. Its purpose is to evaluate the truth that a claim X is supported by evidence Y. This paper exposes some flaws with how the original unification function handles belief, possibility, and inconsistency. By making changes to the function this paper allows both interval and point-value semantic unification to be used in a more consistent and intuitive way.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2006.05.006