UAI 1987
A Bayesian Perspective on Confidence
Abstract
We present a representation of partial confidence in belief and preference that is consistent with the tenets of decision-theory. The fundamental insight underlying the representation is that if a person is not completely confident in a probability or utility assessment, additional modeling of the assessment may improve decisions to which it is relevant. We show how a traditional decision-analytic approach can be used to balance the benefits of additional modeling with associated costs. The approach can be used during knowledge acquisition to focus the attention of a knowledge engineer or expert on parts of a decision model that deserve additional refinement.
Authors
Keywords
Context
- Venue
- Conference on Uncertainty in Artificial Intelligence
- Archive span
- 1985-2025
- Indexed papers
- 3717
- Paper id
- 576472785767042297