Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge (Artificial Intelligence Series) - Softcover

Kuipers, Benjamin

Softcover

ISBN 10: 0262515407 ISBN 13: 9780262515405

Verlag: MIT Press, 2003

Inhaltsangabe

A body of methods that have been developed for building and simulating qualitative models of physical systems where knowledge of that system is incomplete.

This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed for building and simulating qualitative models of physical systems—bathtubs, tea kettles, automobiles, the physiology of the body, chemical processing plants, control systems, electrical systems—where knowledge of that system is incomplete.The primary tool for this work is the author's QSIM algorithm, which is discussed in detail. Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model.This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence. The framework is built around the QSIM algorithm for qualitative simulation and the QSIM representation for qualitative differential equations, both of which are carefully grounded in continuous mathematics. Qualitative simulation draws on a wide range of mathematical methods to keep a complete set of predictions tractable, including the use of partial quantitative information. Compositional modeling and component-connection methods for building qualitative models are also discussed in detail.

Qualitative Reasoning is primarily intended for advanced students and researchers in AI or its applications. Scientists and engineers who have had a solid introduction to AI, however, will be able to use this book for self-instruction in qualitative modeling and simulation methods.

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Reseña del editor

A body of methods that have been developed for building and simulating qualitative models of physical systems where knowledge of that system is incomplete. This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed for building and simulating qualitative models of physical systems-bathtubs, tea kettles, automobiles, the physiology of the body, chemical processing plants, control systems, electrical systems-where knowledge of that system is incomplete.The primary tool for this work is the author's QSIM algorithm, which is discussed in detail. Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model.This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence. The framework is built around the QSIM algorithm for qualitative simulation and the QSIM representation for qualitative differential equations, both of which are carefully grounded in continuous mathematics. Qualitative simulation draws on a wide range of mathematical methods to keep a complete set of predictions tractable, including the use of partial quantitative information. Compositional modeling and component-connection methods for building qualitative models are also discussed in detail. Qualitative Reasoning is primarily intended for advanced students and researchers in AI or its applications. Scientists and engineers who have had a solid introduction to AI, however, will be able to use this book for self-instruction in qualitative modeling and simulation methods.

Biografía del autor

Daniel G. Bobrow is a Research Fellow in the Intelligent Systems Laboratory, Xerox Palo Alto Research Center, editor-in-chief of the Journal of Artificial Intelligence, and Chair of the Governing Board of the Cognitive Science Society. Michael Brady is Senior Research Scientist at MIT's Artifical Intelligence Laboratory. Patrick H. Winston is Professor of Electrical Engineering and Computer Science and Director of the Artificial Intelligence Laboratory at MIT.

Details zur Ausgabe

• Verlag: MIT Press
• Erscheinungsdatum: 2003
• Sprache: Englisch
• ISBN 10: 0262515407
• ISBN 13: 9780262515405
• Einband: Tapa blanda
• Anzahl der Seiten: 456
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Purmerul LTD; https://strengholt.nl/en/; ; 22 Liuleburgaz Str., floor 4, app. 9; Plovdiv; Bulgarien