Abductive Inference Models for Diagnostic Problem-Solving
Produktnummer:
18d51512684573423d9b709c7773ebeda4
| Autor: | Peng, Yun Reggia, James A. |
|---|---|
| Themengebiete: | algorithms artificial intelligence classification cognitive science intelligence neural network problem solving search algorithm |
| Veröffentlichungsdatum: | 26.06.1990 |
| EAN: | 9780387973432 |
| Sprache: | Englisch |
| Seitenzahl: | 285 |
| Produktart: | Gebunden |
| Verlag: | Springer US |
Produktinformationen "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.
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