Case-Based Approximate Reasoning (Hardcover, 2007 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Theory and Decision Library B, 44
Release date:	2007
First published:	2007
Authors:	Eyke Hullermeier
Dimensions:	235 x 155 x 22mm (L x W x T)
Format:	Hardcover
Pages:	372
Edition:	2007 ed.
ISBN-13:	978-1-4020-5694-9
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	1-4020-5694-X
Barcode:	9781402056949

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!