Logic for Learning : Learning Comprehensible Theories from Structured Data
Softcover reprint of hardcover 1st ed. 2003
Book Details
Format
Paperback / Softback
Book Series
Cognitive Technologies
ISBN-10
3642075533
ISBN-13
9783642075537
Edition
Softcover reprint of hardcover 1st ed. 2003
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Oct 22nd, 2010
Print length
257 Pages
Weight
420 grams
Dimensions
15.80 x 23.40 x 1.80 cms
Ksh 8,100.00
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This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. For those in computational logic, no previous knowledge of machine learning is assumed and, for those in machine learning, no previous knowledge of computational logic is assumed.
This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those interested in computational logic, it provides a framework for knowledge representation and computation based on higher-order logic, and demonstrates its advantages over more standard approaches based on first-order logic. For those interested in machine learning, the book explains how higher-order logic provides suitable knowledge representation formalisms and hypothesis languages for machine learning applications.
Get Logic for Learning by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG and it has pages.
