Abstract
Abduction is a type of logic or reasoning which derives plausible explanations for the data at hand. In this book, formal and computational models of the abductive reasoning process that underlies diagnostic problem- solving are considered. The core material presented is that of “parsimonious covering theory” and various extensions to it. Among other things, this theory provides a theoretical foundation for the recent and continuing efforts to automate abductive reasoning in diagnostic problem-solving.
“Ah, my dear Watson, there we come to the realms of conjecture where the most logical mind may be at fault. Each may form his own hypothesis upon the present evidence, and yours is as likely to be correct as mine.”
Arthur C. Doylr, The Empty House
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© 1990 Springer Science+Business Media New York
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Peng, Y., Reggia, J.A. (1990). Abduction and Diagnostic Inference. In: Abductive Inference Models for Diagnostic Problem-Solving. Symbolic Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8682-5_1
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DOI: https://doi.org/10.1007/978-1-4419-8682-5_1
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-6450-7
Online ISBN: 978-1-4419-8682-5
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