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Abductive Inference Models for Diagnostic Problem-Solving

  • Yun Peng
  • James A. Reggia

Part of the Symbolic Computation book series (SYMBOLIC)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Yun Peng, James A. Reggia
    Pages 1-10
  3. Yun Peng, James A. Reggia
    Pages 11-47
  4. Yun Peng, James A. Reggia
    Pages 49-98
  5. Yun Peng, James A. Reggia
    Pages 99-147
  6. Yun Peng, James A. Reggia
    Pages 149-199
  7. Yun Peng, James A. Reggia
    Pages 201-226
  8. Yun Peng, James A. Reggia
    Pages 227-253
  9. Yun Peng, James A. Reggia
    Pages 255-268
  10. Back Matter
    Pages 269-285

About this book

Introduction

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.

Keywords

algorithms artificial intelligence classification cognitive science intelligence neural network problem solving search algorithm

Authors and affiliations

  • Yun Peng
    • 1
    • 2
  • James A. Reggia
    • 1
  1. 1.Department of Computer ScienceUniversity of MarylandCollege ParkUSA
  2. 2.The Institute of SoftwareAcademia SinicaBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-8682-5
  • Copyright Information Springer-Verlag New York Inc. 1990
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-6450-7
  • Online ISBN 978-1-4419-8682-5
  • Buy this book on publisher's site