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Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge

AUTHOR: Benjamin Kuipers
ISBN: 026211190X

SHORT DESCRIPTION: This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past fifteen years for building and simulating qualitative models of physical systems - bathtubs, tea kettles,...

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Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge
- Book Review,
by Benjamin Kuipers

From Book News, Inc.
Presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past 15 years 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 the system is incomplete. The primary tool for this work is the author's QSIM algorithm, which is discussed in detail. Annotation copyright Book News, Inc. Portland, Or.

Book Description
This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past fifteen years 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. Artificial Intelligence series

Book Info
Presents within a conceptually unified theoretical framework a body of methods that have been developed over the past fifteen years for building and simulating qualitative models of physical systems. DLC: Artificial intelligence.

About the Author
Benjamin Kuipers is Bruton Centennial Professor of Computer Science at the University of Texas at Austin.


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         Book Review

Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge
- Book Reviews,
by Benjamin Kuipers

Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge

FROM THE PUBLISHER

This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past fifteen years 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.

FROM THE CRITICS

Booknews

Presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past 15 years 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 the system is incomplete. The primary tool for this work is the author's QSIM algorithm, which is discussed in detail. Annotation c. Book News, Inc., Portland, OR (booknews.com)


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