Inference Methods and Uncertainty [1]

This presentation shows you how the components of an expert system interact to provide advice. The reasoning mechanisms used by the inference engine to process rules in the knowledge base and the techniques used to manipulate uncertain data are described.
Forward chaining (data driven) and backward chaining (hypothesis driven) techniques represent the fundamental reasoning approaches implemented in rule-based expert systems. These will be introduced using a simulation of the expert system model shown above along with a simplified representation of the "auto diagnosis" advising problem that provided a framework for the introductory tutorial.

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