Abductive Inference Models for Diagnostic Problem-Solving

Making a diagnosis when something goes wrong with a natural or m- made system can be difficult. In many fields, such as medicine or electr- 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 knowledge in arriving at a conclusion or a diagnosis, except perhaps implicitly through ease examples. This would seem to indicate that many of the essential aspects of diagnostic reasoning are a type of intuiti- based, common sense reasoning. More precisely, diagnostic reasoning can be classified as a type of 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.

Summary

This would seem to indicate that many of the essential aspects of diagnostic reasoning are a type of intuiti- based, common sense reasoning. More precisely, diagnostic reasoning can be classified as a type of inf- ence known as abductive reasoning or abduction.

Product details

• Authors: James A. Reggia, Yun Peng, James A Reggia, Yu Peng
• Publisher: Springer, Berlin
• Content: Book
• Product form: Hardback
• Publication date: 01.07.2009
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT
• EAN: 9780387973432
• ISBN: 978-0-387-97343-2
• Pages: 285
• Illustrations: XII, 285 p.
• Height (packing): 23.5 cm
• Weight (packing): 599 g
• Series: Artificial Intelligence; Symbolic computation/Artificial Intelligence; Symbolic Computation; Artificial Intelligence; Symbolic Computation