A model for an expert system to update states of uncertainty in decision making
Jacqueline Beth Schuster · 1991
This work presents a model of probability calculation for decision making in uncertain situations. It uses causal relationships to build a graphical network from which probabilistic independence relationships can be determined. Probabilities are stored as distributions rather than as single numbers. These distributions can be used to guide data acquisition of node and parameter values as well as to calculate and update probability values. The objective of this work is to improve the quality of decision making by making it easier to incorporate probabilistic analysis into the decision analysis, and to show how this same probabilistic analysis can be used to guide data acquisition.