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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