Yun Peng, James A. Reggia

Abductive Inference Models for Diagnostic Problem-Solving

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Artificial Intelligence
• Verlag: Springer / Springer New York / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4612-6450-7
• Softcover reprint of the original 1st ed. 1990
• Seitenzahl: 300
• Erscheinungstermin: 20. November 2012
• Englisch
• Abmessung: 235mm x 155mm x 17mm
• Gewicht: 476g
• ISBN-13: 9781461264507
• ISBN-10: 1461264502
• Artikelnr.: 39492665

Inhaltsangabe

1 Abduction and Diagnostic Inference.- 2 Computational Models for Diagnostic Problem Solving.- 3 Basics of Parsimonious Covering Theory.- 4 Probabilistic Causal Model.- 5 Diagnostic Strategies in the Probabilistic Causal Model.- 6 Causal Chaining.- 7 Parallel Processing for Diagnostic Problem-Solving.- 8 Conclusion.