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.
| Autorius: | James A. Reggia, Yun Peng, |
| Serija: | Artificial Intelligence |
| Leidėjas: | Springer New York |
| Išleidimo metai: | 2012 |
| Knygos puslapių skaičius: | 300 |
| ISBN-10: | 1461264502 |
| ISBN-13: | 9781461264507 |
| Formatas: | 235 x 155 x 17 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Abductive Inference Models for Diagnostic Problem-Solving“
