Overview

Full Product Details

Author:   John W. Lloyd
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of hardcover 1st ed. 2003
Dimensions:   Width: 15.50cm , Height: 1.40cm , Length: 23.50cm
Weight:   0.454kg
ISBN:  

9783642075537

ISBN 10:   3642075533
Pages:   257
Publication Date:   22 October 2010
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Part I: Prologue.- Overview.- Introduction to Learning and Logic.- Part II: Logic.- Higher-order Logic.- Representation of Individuals.- Predicate Construction.- Programming with Equational Theories.- Part III: Learning.- The Problem of Learning.- Knowledge Representation for Learning.- Learning Systems.- Illustrations for Various Types.- Applications.- References.- Notation.- Index.

Reviews

From the reviews of the third edition: John has tried his hand at machine learning, and his aim in Logic for Learning is to demonstrate 'the rich and fruitful interplay between the fields of computational logic and machine learning'. ! As such, the book is more geared towards computational logicians who are interested in machine learning ! . The book can also be used as a textbook in a mathematically oriented advanced graduate course. ! it is indeed great stuff, which deserves to be taken serious by any computational logician ! . (Peter Flach, TLP -- Theory and Practice of Logic Programming, Issue 4, 2004) From the reviews: This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. It is aimed at researchers, graduate students, and senior undergraduates working in computational logic and/or machine learning. (PHINEWS, Vol. 3, April, 2003)

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