This book is about reasoning with causal associations during diagnostic problem-solving. It formalizes several currently vague notions of abductive inference in the context of diagnosis. The result is a mathematical model of diagnostic reasoning called parsimonious covering theory. Within this diagnostic, problems and important relevant concepts are formally defined, properties of diagnostic problem-solving are identified and analyzed, and algorithms for finding plausible explanations in different situations are given along with proofs of their correctness. Another feature of this book is the integration of parsimonious covering theory and probability theory. Based on underlying cause-effect relations, the resulting probabilistic causal model generalized Bayesian classification to diagnostic problems where multiple disorders (faults) may occur simultaneously. Both sequential best-first search algorithms and parallel connectionist (neural network) algorithms for finding the most probable hypothesis are provided. This book should appeal to both theoretical researchers and practitioners. For researchers in artificial intelligence and cognitive science, it provides a coherent presentation of a new theory of diagnostic inference. For engineers and developers of automated diagnostic systems or systems solving other abductive tasks, the book may provide useful insights, guidance, or even directly workable algorithms.
Abductive Inference Models for Diagnostic Problem-Solving
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First Sentence:
Abduction is a type of logic or reasoning which derives plausible explanations for the data at hand. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
Chemical Spill System, Mathematical Appendix, Related Work, Carbonic Acid Benzenesulfonic Acid Competing, Cogan's Syndrome, Frontier Candidates, Frontier Frontier, Generality of the Theory, Labyrinthine Fistula, Month of Year, Ready For Command Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Abduction is a type of logic or reasoning which derives plausible explanations for the data at hand. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
Chemical Spill System, Mathematical Appendix, Related Work, Carbonic Acid Benzenesulfonic Acid Competing, Cogan's Syndrome, Frontier Candidates, Frontier Frontier, Generality of the Theory, Labyrinthine Fistula, Month of Year, Ready For Command Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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This book cites 36
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13
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- Principles of Artificial Intelligence by Nils J. Nilsson in Front Matter, and Back Matter
- Pattern Classification (2nd Edition) by Richard O. Duda on page 14, and Back Matter
- Problem Solving (Brooks/Cole One-Unit Series in Precalculus Mathematics) by Karl J. Smith in Back Matter (1), and Back Matter (2)
- Problem Solving (Teacher Timesavers) by Jill Bennett in Back Matter (1), and Back Matter (2)
- Artificl Intell Instructrs Manual Tx by Author Unknown in Front Matter, and Back Matter
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- Scientific Innovation, Philosophy, and Public Policy: Volume 13, Part 2 (Social Philosophy and Policy) (Vol 13, Pt.2) by Ellen Frankel Paul on page 233
- Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence) by Ronald Brachman in Back Matter
- Research Perspectives and Case Studies in Systems Test and Diagnosis (Frontiers in Electronic Testing) by John W. Sheppard on page 164
- Widerspruch Und Widerstandigkeit: Zur Darstellung Und Pragung Raumlicher Vollzuge Personaler Idnetitat (Theilogische Bibliothek Topelmann) (German Edition) by Asha De on page 349
- Intelligent Information Processing II: IFIP TC12/WG12.3 International Conference on Intelligent Information Processing (IIP2004) October 21-23, 2004, ... in Information and Communication Technology) by Qing He on page 430
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