Current Search: Lantigua, Jose Salvador. (x)
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Title
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Transforming directed graphs into uncertain rules.
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Creator
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Lantigua, Jose Salvador., Florida Atlantic University, Hoffman, Frederick, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
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Abstract/Description
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The intent of this thesis is to show how rule structures can be derived from influence diagrams and how these structures can be mapped to existing rule-based shell paradigms. We shall demonstrate this mapping with an existing shell having the Evidence (E) --> Hypothesis (H), Certainty Factor (CF) paradigm structure. Influence diagrams are graphical representations of hypothesis to evidence, directed forms of Bayesian influence networks. These allow for inferencing about both diagnostic and...
Show moreThe intent of this thesis is to show how rule structures can be derived from influence diagrams and how these structures can be mapped to existing rule-based shell paradigms. We shall demonstrate this mapping with an existing shell having the Evidence (E) --> Hypothesis (H), Certainty Factor (CF) paradigm structure. Influence diagrams are graphical representations of hypothesis to evidence, directed forms of Bayesian influence networks. These allow for inferencing about both diagnostic and predictive (or causal) behavior based on uncertain evidence. We show how this can be implemented through a Probability (P) to CF mapping algorithm and a rule-set conflict resolution methodology. The thesis contains a discussion about the application of probabilistic semantics from Bayesian networks and of decision theory, to derive qualitative assertions about the likelihood of an occurrence; the sensitivity of a conclusion; and other indicators of usefulness. We show an example of this type of capability by the addition of a probability range function for the premise clause in our shell's rule structure.
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Date Issued
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1989
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PURL
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http://purl.flvc.org/fcla/dt/14570
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Subject Headings
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Decision-making--Mathematical models, Probabilities, Expert systems (Computer science)
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Format
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Document (PDF)
