Titlebook: Abductive Inference Models for Diagnostic Problem-Solving; Yun Peng,James A. Reggia Book 1990 Springer Science+Business Media New York 199

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ics, a long training period and apprenticeship are required to become a skilled diagnostician. During this time a novice diagnostician is asked to assimilate a large amount of knowledge about the class of systems to be diagnosed. In contrast, the novice is not really taught how to reason with this k

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Gerhard A. Stadler,Manfred Wehdorn explanation, and very importantly, the process of hypothesize-and- test reasoning. Our ultimate goal is to derive a formal model that captures a significant part of the causal knowledge and inference method described in the previous chapters.

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Gerhard A. Stadler,Manfred Wehdornes (in some problems the number of irredundant covers of the given .. may be fairly large). The relative likelihood measure may be used to overcome this difficulty if we redefine the problem solution as the hypothesis with the highest relative likelihood value, i.e., the most probable one.

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Gerhard A. Stadler,Manfred Wehdornd thus may find applications for some non- diagnostic problems. The potential generality of this theory is discussed in Section 8.2, along with some of its non-diagnostic applications. Finally, in Section 8.3, we outline some limitations and potential extensions to the current form of this formal model.

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Book 1990 inf- ence known as abductive reasoning or abduction. Abduction is defined to be a process of generating a plausible explanation for a given set of obs- vations or facts. Although mentioned in Aristotle‘s work, the study of f- mal aspects of abduction did not really start until about a century ago.

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