(Enter summary)
Abstract: Researchers in artificial intelligence and decision analysis share a concern with the construction of formal models of human knowledge and expertise. Historically, however, their approaches to these problems have diverged. Members of these two communities have recently discovered common ground: a family of graphical models of decision theory known as influence diagrams or as belief networks. These models are equally attractive to theoreticians, decision modelers, and designers of... (Update)
Context of citations to this paper: More
...development. The most important practical methods for modelling uncertain decision situations are decision trees and influence diagrams [48, 54], and more recent sequential decision diagrams [21] which all in turn use probabilities and density functions to model the underlying...
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BibTeX entry: (Update)
Matzkevich, Izhar; Abramson, Bruce; 1995; "Decision Analytic Networks in Artificial Intelligence"; Management Science, Vol.41 http://citeseer.ist.psu.edu/izhar95decision.html More
@article{ matzkevich95.decision,
author = "I. Matzkevich and B. Abramson",
title = "Decision Analytic Networks In Artificial Intelligence",
year = "1995",
journal = "Management Science",
volume = "41",
number = "1",
pages = "1-22",
url = "citeseer.ist.psu.edu/izhar95decision.html" }
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