Approximate Reasoning for Processing Uncertainty | Zendy

Hamid Séridi | Zendy; Herman Akdag | Zendy

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Approximate Reasoning for Processing Uncertainty

Author(s) -

Hamid Séridi,

Herman Akdag

Publication year - 2001

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2001.p0110

Subject(s) - computer science , axiom , usable , axiomatic system , division (mathematics) , bayesian network , set (abstract data type) , qualitative reasoning , multiplication (music) , theoretical computer science , artificial intelligence , bayesian probability , mathematics , arithmetic , programming language , geometry , combinatorics , world wide web

In Bayesian networks as well as in knowledge-based systems, uncertainty in propositions can be represented by various degrees of belief encoded by qualitative values. In this paper, we present a qualitative approach of classical probability theory in the particular case where the set of probability degrees is replaced by a totally ordered set of symbolic values. We first define the four elementary operations (addition, subtraction, multiplication and division) allowing to manipulate these symbolic degrees of uncertainty, then we propose an axiomatic. The properties obtained from this axiomatic allows to show that our theory constitutes a qualitative approach for processing uncertain statements of natural language. The obtained results are usable in inferential processes as well as in Bayesian networks.

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