Operations Research
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Decision analysis and expert systems
AI Magazine
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A Guide to the Literature on Learning Probabilistic Networks from Data
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Knowledge Organisation in a Neonatal Jaundice Decision Support System
ISMDA '01 Proceedings of the Second International Symposium on Medical Data Analysis
Modeling challenges with influence diagrams: Constructing probability and utility models
Decision Support Systems
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We have recently introduced a method for minimising the storage space of huge decision tables faced after solving real-scale decision-making problems under uncertainty [4]. In this paper, the method is combined with a proposal of a query system to answer expert questions about the preferred action, for a given instantiation of decision table attributes. The main difficulty is to accurately answer queries associated with incomplete instantiations. Moreover, the decision tables often only include a subset of the whole problem solution due to computational problems, leading to uncertain responses. Our proposal establishes an automatic and interactive dialogue between the decision support system and the expert to extract information from the expert to reduce uncertainty. Typically, the process involves learning a Bayesian network structure from a relevant part of the decision table and the computation of some interesting conditional probabilities that are revised accordingly.