Ebook: Abductive Inference Models for Diagnostic Problem-Solving
Author: Yun Peng James A. Reggia (auth.)
- Tags: Artificial Intelligence (incl. Robotics)
- Series: Symbolic Computation
- Year: 1990
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
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.
Content:
Front Matter....Pages i-xii
Abduction and Diagnostic Inference....Pages 1-10
Computational Models for Diagnostic Problem Solving....Pages 11-47
Basics of Parsimonious Covering Theory....Pages 49-98
Probabilistic Causal Model....Pages 99-147
Diagnostic Strategies in the Probabilistic Causal Model....Pages 149-199
Causal Chaining....Pages 201-226
Parallel Processing for Diagnostic Problem-Solving....Pages 227-253
Conclusion....Pages 255-268
Back Matter....Pages 269-285
Content:
Front Matter....Pages i-xii
Abduction and Diagnostic Inference....Pages 1-10
Computational Models for Diagnostic Problem Solving....Pages 11-47
Basics of Parsimonious Covering Theory....Pages 49-98
Probabilistic Causal Model....Pages 99-147
Diagnostic Strategies in the Probabilistic Causal Model....Pages 149-199
Causal Chaining....Pages 201-226
Parallel Processing for Diagnostic Problem-Solving....Pages 227-253
Conclusion....Pages 255-268
Back Matter....Pages 269-285
....