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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14265
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| Title: | Ratio-Scale Elicitation of Degrees of Support |
| Authors: | Schocken, Shimon |
| Issue Date: | 1993 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-93-29 |
| Abstract: | During the last decade, the computational paradigms known as inflzcence
diagrams and belief networks have become to dominate the diagnostic
expert systems field. Using elaborate collections of nodes and arcs,
these representations describe how propositions of interest interact
with each other through a variety of causal and predictive links. The
links are parameterized with inexact degrees of support, typically
expressed as subjective conditional probabilities or likelihood ratios.
To date, most of the research in this area has focused on developing
efficient belief-revision calculi to support decision making under
uncertainty. Taking a different perspective, this paper focuses on the
inputs of these calculi, i.e. on the human-supplied degrees of support
which provide the currency of the belief revision process. Traditional
methods for eliciting subjective probability functions are of little use
in rule-based settings, where propositions of interest represent
causally related and mostly discrete random variables. We describe
ratio-scale and graphical methods for (i) eliciting degrees of support
from human experts in a credible manner, and (ii) transforming them into
the conditional probabilities and likelihood-ratios required by standard
belief revision algorithms. As a secondary contribution, the paper
offers a new graphical justification to eigenvector techniques for
smoothing subjective answers to pair-wise elicitation questions. |
| URI: | http://hdl.handle.net/2451/14265 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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