A linear programming framework for logics of uncertainty

Several logics for reasoning under uncertainty distribute “probability mass” over sets in some sense. These include probabilistic logic, Dempster-Shafer theory, other logics based on belief functions, and second-order probabilistic logic. We show that these logics are instances of a certain type of...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Decision Support Systems Ročník 16; číslo 1; s. 39 - 53
Hlavní autoři: Andersen, K.A., Hooker, J.N.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 1996
Elsevier Sequoia S.A
Témata:
Decision support systems
Linear programming
Logic
Probability
Uncertainty
Logic
Linear programming
Uncertainty
ISSN:0167-9236, 1873-5797
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Several logics for reasoning under uncertainty distribute “probability mass” over sets in some sense. These include probabilistic logic, Dempster-Shafer theory, other logics based on belief functions, and second-order probabilistic logic. We show that these logics are instances of a certain type of linear programming model, typically with exponentially many variables. We also show how a single linear programming package can implement these logics computationally if one “plugs in” a different column generation subroutine for each logic, although the practicality of this approach has been demonstrated so far only for probabilistic logic.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
ISSN:0167-9236
1873-5797
DOI:10.1016/0167-9236(94)00055-7