by North-Holland, Sole distributors for the U.S.A. and Canada, MIT Press in Amsterdam, New York, Cambridge, MA .
|Other titles||Physical systems.|
|Statement||edited by Daniel G. Bobrow.|
|Contributions||Bobrow, Daniel Gureasko.|
|LC Classifications||Q335.5 .Q35 1984|
|The Physical Object|
|Pagination||491 p. :|
|Number of Pages||491|
|LC Control Number||84024675|
Qualitative Reasoning about Physical Systems [D. G. Bobrow] on judybwolfman.com *FREE* shipping on qualifying offers. This volume brings together current work on qualitative reasoning. Its publication reflects the maturity of qualitative reasoning as a research area and the growing interest in problems of reasoning about physical systems. The papers present knowledge bases for a number of very. Qualitative Reasoning about Physical Systems (Special Issues of [Daniel G. Bobrow] on judybwolfman.com *FREE* shipping on qualifying offers. Complex machines are used, understood and repaired by people with essentially no formal training in physics and engineering-although the design and manufacture of such machines requires a deep knowledge of these subjects. Qualitative reasoning about physical systems. Abstract. No abstract available. Cited By. Hinkkanen A, Lang K and Whinston A () A Set-Theoretical Foundation of Qualitative Reasoning and its Application to the Modeling of Economics and Business . Qualitative Reasoning (QR) is an area of research within Artificial Intelligence (AI) that automates reasoning about continuous aspects of the physical world, such as space, time, and quantity, for the purpose of problem solving and planning using qualitative rather than quantitative information.
Qualitative reasoning about physical systems / D.G. Bobrow --A qualitative physics based on confluences / J. de Kleer and J.S. Brown --Qualitative process theory / K.D. Forbus --Commonsense reasoning about causality / B. Kuipers --How circuits work / J. de Kleer --Qualitative analysis of MOS circuits / B.C. Williams --Diagnostic reasoning based. This volume brings together current work on qualitative reasoning. Its publication reflects the maturity of qualitative reasoning as a research area and the growing interest in problems of reasoning about physical systems. The papers present knowledge bases for a number of very different domains, including heat flow, transistors, and digital. 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. A model for integrated qualitative spatial and dynamic reasoning about physical systems. In Proceedings of the National Conference on Artificial Intelligence (AAAI), AAAI/MIT Press, Raman Rajagopalan. Qualitative reasoning about dynamic change in .
R. Greg Arbon, Laurie Atkinson, James Chen, Chris A. Guida, TPF dump analyzer: a system to provide expert assistance to analysts in solving run-time program exceptions by deriving program intention from a TPF assembly language program, Proceedings of the fourth conference on Innovative applications of artificial intelligence, p, July , , San Jose, CaliforniaCited by: This collection of articles, which constituted a special issue of the Journal of Artificial Intelligence, presents the most recent work on qualitative reasoning about the real (physical) world. 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. Areas of application are physics, medicine, the field of ecology, process control, etc. In addition to the classification of existing methods, the book presents a new approach based on fuzzy sets. And the work relates Qualitative Reasoning with such fields of Expert Systems, System Theory and Cognitive Science.