Title :
Uncertain if-then rules based on mathematical conditionals
Author_Institution :
Dept. of Math. Sci., New Mexico State Univ., Las Cruces, NM, USA
Abstract :
The modeling of uncertainty involved in production rules in expert systems is considered. A possibilistic approach to modeling of uncertainty in production rules of the form if...then is discussed. It is shown that conditional inference in possibility theory is compatible with the newly developed theory of measure-free conditionals. Thus, conditional events provide a foundation for possibilistic reasoning. The domain of applicability of possibility theory is outlined and the relation with probabilistic modeling is investigated
Keywords :
expert systems; fuzzy logic; fuzzy set theory; model-based reasoning; probabilistic logic; probability; uncertainty handling; conditional inference; expert systems; possibilistic reasoning; possibility theory; probabilistic modeling; uncertain if-then rules; uncertainty; Boolean algebra; Calculus; Expert systems; Fuzzy reasoning; Knowledge representation; Logic; Polynomials; Possibility theory; Probability; Production systems;
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
DOI :
10.1109/FUZZY.1992.258677