Case-Based Approximate Reasoning - Couverture souple

H�llermeier, Eyke

9789048174317: Case-Based Approximate Reasoning

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ISBN 10 : 9048174317 ISBN 13 : 9789048174317

Editeur : Springer, 2013

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Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'.

Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.

This books is suitable for researchers and practioners in the fields of artifical intelligence, knowledge engineering and knowledge-based systems.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer
Date d'�dition: 2013
Langue: anglais
ISBN 10: 9048174317
ISBN 13: 9789048174317
Reliure: Broch�
Nombre de pages: 388
Coordonn�es du fabricant: non disponible
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9781402056949: Case-Based Approximate Reasoning

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ISBN 10 : 140205694X ISBN 13 : 9781402056949
Editeur : Springer-Verlag New York Inc., 2007
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Case-Based Approximate Reasoning

Eyke H�llermeier

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ISBN 10 : 9048174317 ISBN 13 : 9789048174317

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Major contribution to the methodical foundations of case-based reasoningBuilds bridges between the fields of CBR and approximate reaoningFirst monograph of this typeMaking use of different frameworks of approximate reasoning . N� de r�f. du vendeur 5821271

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Case-Based Approximate Reasoning

Eyke H�llermeier

Edit� par Springer Netherlands Jan 2013, 2013

ISBN 10 : 9048174317 ISBN 13 : 9789048174317

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. 388 pp. Englisch. N� de r�f. du vendeur 9789048174317

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Case-Based Approximate Reasoning (Theory and Decision Library B, 44)

H�llermeier, Eyke

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ISBN 10 : 9048174317 ISBN 13 : 9789048174317

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Case-Based Approximate Reasoning

Eyke H�llermeier

Edit� par Springer Netherlands, Springer Netherlands, 2013

ISBN 10 : 9048174317 ISBN 13 : 9789048174317

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'.Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.This books is suitable for researchers and practioners in the fields of artifical intelligence, knowledge engineering and knowledge-based systems. N� de r�f. du vendeur 9789048174317

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Case-Based Approximate Reasoning

Eyke H�llermeier

Edit� par Springer Netherlands, Springer Netherlands Jan 2013, 2013

ISBN 10 : 9048174317 ISBN 13 : 9789048174317

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'.Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.This books is suitable for researchers and practioners in the fields of artifical intelligence, knowledge engineering and knowledge-based systems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch. N� de r�f. du vendeur 9789048174317

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