Published by Lawrence Erlbaum Associates, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Published by Lawrence Erlbaum Assoc Inc, Mahwah, New Jersey, U.S.A., 1997
ISBN 10: 0805823123 ISBN 13: 9780805823127
Language: English
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Add to basketHard Cover. Condition: Very Good. 342 pages. The book is a little worn. Books listed here are not stored at the shop. Please contact us if you want to pick up a book from Newtown. Size: Size F: 9"-10" Tall (228-254mm).
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Published by Taylor & Francis Group, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Published by Taylor & Francis Inc, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Published by Psychology Press 1997-01-04, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Published by Taylor & Francis Group, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Published by Lawrence Erlbaum Assoc Inc, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Published by Psychology Press 1997-05-13, 1997
ISBN 10: 0805823123 ISBN 13: 9780805823127
Language: English
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Published by Taylor & Francis Group, 1997
ISBN 10: 0805823123 ISBN 13: 9780805823127
Language: English
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Published by Taylor & Francis Group, 1997
ISBN 10: 0805823123 ISBN 13: 9780805823127
Language: English
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Published by Taylor & Francis Group, 1997
ISBN 10: 0805823131 ISBN 13: 9780805823134
Language: English
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Mary Lou Maher, Pearl PuDesign is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning technique.
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Design is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning techniques have been applied to build design automation and/or design decision support systems. Although such systems have met with some success, difficulties have been encountered in terms of formalizing such generalized design experiences as rules, logic, and domain models. Recently, researchers have been exploring the idea of using case-based reasoning (CBR) techniques to complement or replace other approaches to design support.CBR can be considered as an alternative to paradigms such as rule-based and model-based reasoning. Rule-based expert systems capture knowledge in the form of if-then rules which are usually identified by a domain expert. Model-based reasoning aims at formulating knowledge in the form of principles to cover the various aspects of a problem domain. These principles, which are more general than if-then rules, comprise a model which an expert system may use to solve problems. Model-based reasoning (MBR) is sometimes called reasoning from first principles. Instead of generalizing knowledge into rules or models, CBR is an experience-based method. Thus, specific cases, corresponding to prior problem-solving experiences, comprise the main knowledge sources in a CBR system.This volume includes a collection of chapters that describe specific projects in which case-based reasoning is the focus for the representation and reasoning in a particular design domain. The chapters provide a broad spectrum of applications and issues in applying and extending the concept of CBR to design. Each chapter provides its own introduction to CBR concepts and principles.
Published by Taylor & Francis Group, 1997
ISBN 10: 0805823123 ISBN 13: 9780805823127
Language: English
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Seller: moluna, Greven, Germany
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Mary Lou Maher, Pearl PuDesign is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning technique.