Wl. Perry et He. Stephanou, A QUANTITATIVE TREATMENT OF MULTILEVEL SPECIFICITY AND UNCERTAINTY INVARIABLE PRECISION REASONING, IEEE transactions on systems, man, and cybernetics, 23(2), 1993, pp. 445-451
Citations number
10
Categorie Soggetti
Controlo Theory & Cybernetics","Computer Applications & Cybernetics
Decision making under uncertainty requires that we mason about the tru
e nature of the environment using perceived information that is usuall
y incomplete and often ambiguous. Consequently, the reasoning process
varies with the quality of the evidence the decision maker receives. I
f the evidence can be represented as a probability mass function defin
ed on the discrete set of hypotheses about the environment, then its q
uality is dependent upon its ability to suggest clear choices among th
e hypotheses. This is measured by the use of an indistinguishability m
easure that focuses on the degree to which the hypotheses are similar
to each other and the closeness of their probability support levels. T
he two aspects of variable precision reasoning, specificity and certai
nty, are addressed through the transformation of the basic probability
mass function on the set of hypotheses into a belief function. The be
lief function core set consists of aggregate disjunctive sets of hypot
heses that reflect the degree of specificity present in the evidence.
The set of basic probability assessments on the core establishes the d
egree of certainty associated with the derived level of specificity. T
he aggregation process is accomplished by applying the indistinguishab
ility measure to the set of hypotheses. The core set is grown iterativ
ely using binary set representations of the focal elements. The basic
probability assessments are calculated using a fuzzy partial dominance
measure that diffuses belief in a focal element in proportion to the
number of basic hypotheses it is dose to.