Some knowledge-acquisition methods for prospector-like systems

摘要

The paper deals with the knowledge-acquisition methods designed and tested under the FEL-EXPERT Project, which is aimed at the development of rule-based diagnostic shells. Three different approaches have been used for knowledge acquisition: pattern-recognition, decision-tree, and intensional, pure probabilistic approaches. The designed methods may be applied to a wide subclass of rule-based diagnostic systems that exploit the pseudo-Bayesian model for uncertainty handling. The experimental results are discussed.