SAMPLING-BASED ROBUST INFERENCE FOR DECISION SUPPORT SYSTEM

摘要

The present invention deals with sampling-based robust inference for decision support systems (DSS). The invention relates to a method of operating a decision support system comprising at least one Bayesian network, to a decision support system and to a computer program product for implementing the system. The system comprising at least one Bayesian network (1), comprising a plurality of nodes (2, 20, 21), each node associated with parameters (4, 200, 210) expressing prior probabilities. At least a subset of the parameters stores a value range (6), and a set of probabilities of interest are calculated based on the parameters. Fig.1