Name
Title | ||
|---|---|---|
Coherent Conditional Probability as a Measure of Uncertainty of the Relevant Conditioning Events |
Abstract | ||
|---|---|---|
In previous papers, by resorting to the most effective concept of conditional probability, we have been able not only to define fuzzy subsets, but also to introduce in a very natural way the basic continuous T-norms and the relevant dual T-conorms, bound to the former by coherence. Moreover, we have given, as an interesting and fundamental by-product of our approach, a natural interpretation of possibility functions, both from a semantic and a syntactic point of view. In this paper we study the properties of a coherent conditional probability looked on as a general non-additive uncertainty measure of the conditioning events, and we prove that this measure is a capacity if and only if it is a possibility. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-45062-7_33 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE |
Keywords | DocType | Volume |
conditional probability | Conference | 2711 |
ISSN | Citations | PageRank |
0302-9743 | 7 | 0.96 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giulianella Coletti | 1 | 572 | 71.49 |
| Romano Scozzafava | 2 | 367 | 48.05 |