Inference Algorithms in Knowledge-Based Systems
This Ch. summarizes some common techniques of inference utilized for fuzzy data. Special attention has been paid to the implementation of modus ponens (which realizes a data-driven mode of reasoning) and modus tollens (corresponding to a goal-driven mode of reasoning). The detachment principle (corresponding to a means of expressing a similarity between fuzzy statements) is also investigated. We discuss how different forms of fuzzy relation equations are used to handle each of these modes of inference. Also the question of a direct link between the relevancy of the KB and the length of the inference chain leading to meaningful conclusions is considered. This is of primordial importance; it has to be analyzed to interpret the results of inference and, in particular, to visualize precision. A proper reformulation of the problem in terms of fuzzy equations makes it possible to consider this knowledge transformation in a greater detail.
KeywordsMembership Function Composition Operator Fuzzy Logic Controller Fuzzy Relation Inference Algorithm
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