A Perspective on Confidence and its use in Focusing Attention During Knowledge Acquisition

UAI-P-1987-PG-123-131 |

In Proceedings of the Third Workshop on Uncertainty in Artificial Intelligence, Seattle, WA (UAI1987)


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.