Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge

Benjamin Kuipers

Cambridge, MA: MIT Press, 1994.
414+xxvii pages. ISBN 0-262-11190-X.


After fifteen years of work, the world of qualitative reasoning according to the QSIM viewpoint is now described in a single book.

Qualitative reasoning is one of the most vigorous areas in artificial intelligence. 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 circuits, and the like) 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 more 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 are important in problem-solving for diagnosis, design, monitoring, and explanation.

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. Qualititative 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.