By Kurt Weichselberger
In this publication the ensuing use of likelihood thought is proposed for dealing with uncertainty in specialist platforms. it's proven that tools violating this recommendation can have harmful outcomes (e.g., the Dempster-Shafer rule and the strategy utilized in MYCIN). the need of a few standards for an accurate combining of doubtful info in professional structures is established and compatible ideas are supplied. the prospect is considered that period estimates are given rather than specified information regarding percentages. For combining details containing period estimates principles are supplied that are beneficial in lots of cases.
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Extra resources for A Methodology for Uncertainty in Knowledge-Based Systems
21) is always possible if the application of the Dempster-Shafer rule is possible. Additionally it can be practiced in those cases, in which PRIs are used, which are feasible, but not D-S-admissible. The extension to more than two sources of information can be achieved stepwise in quite the same manner as for the Dempster-Shafer rule. 21) is not to be seen. Furthermore it is noteworthy that in a way quite similar to that which leads to the Dempster-Shafer rule, another type of combination rule may be derived which does not have the tendency to be too optimistic, but the tendency to be too pessimistic.
2 0 ; P(E4) = U4 = 0 . 5 2 ~ P(E1) = L, = 0 . 0 0 ; P(E3) = U s = 0 . 3 0 ; P(Ea) = 0 . 2 8 : s4 ; P(E~) = U4 = 0 . 18 : t P(E2) = 0 . 2 8 : s5 P(E4) = L4= 0 . 22 : s6 P(E3) = L3 = 0 . 2 0 ; P(E4) = L4 = 0 . 4 8 ~ P(E2) = 0 . 2 2 : sr P(E1) = UI = 0 . 1 0 ; P(E3) = U3 = 0 . 3 0 ; P(E4) = L4 = 0 . 4 8 ~ P(E2) = 0 . 1 2 : ss P(E1) = U1 = 0 . 1 0 ; P(E3) = L 3 = 0 . 2 0 ; P(E4) = U4 = 0 . 5 2 ~ P(E2) = 0 . 1 8 : s9 P(E,) = L1 = 0 . 0 0 ; P(E3) =U3 = 0 . 3 0 ; P(E4) = U4= 0 . 18 P(E2) = L 2 = 0 . 1 0 ; P(E4) = U 4 = O .
3 Theory of Belief Functions In 1975 Glenn Sharer, a student of Dempster's, published "A Mathematical Theory of Evidence". In this book he applied Dempster's theory with respect to two particular aspects: interval-valued probabilities and the combination rule. In this chapter we shall discuss his treatment of interval-valued probabilities. Shafer introduces the concept of belief functions as the fundamental element of his theory. 2 or the lower limit of a probability interval. However, this equivalence is never stated explicitly in Shafer's book.