Articoli correlati a Logic and Learning: Learning Comprehensible Theories...
Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Recensione
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)
Contenuti
1. Introduction.- 2. Logic.- 3. Individuals.- 4. Predicates.- 5. Computation.- 6. Learning.- A. Appendix.- A.1 Well-Founded Sets.- References.- Notation.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra nuovo
Visualizza questo articolo
EUR 47,23
EUR 9,70 per la spedizione da Germania a Italia
Destinazione, tempi e costi
Risultati della ricerca per Logic and Learning: Learning Comprehensible Theories...
Immagini fornite dal venditore
Logic for Learning: Learning Comprehensible Theories from Structured Data (Cognitive Technologies)
Da: Roland Antiquariat UG haftungsbeschränkt, Weinheim, Germania
Valutazione del venditore 5 su 5 stelle
2003. 267 p. Unread book. Like new. 9783540420279 Sprache: Englisch Gewicht in Gramm: 522 Hardcover: 23.4 x 1.6 x 15.6 cm. Codice articolo 201575
Quantità: 1 disponibili
Foto dell'editore
Logic for Learning: Learning Comprehensible Theories from Structured Data.
Editore:
Berlin Springer Verlag, 2003
ISBN 10: 3540420274
ISBN 13: 9783540420279
Antico o usato
Rilegato
Da: CSG Onlinebuch GMBH, Darmstadt, Germania
Valutazione del venditore 5 su 5 stelle
Gebunden. Condizione: Gut. Gebraucht - Gut Zustand: Gut, Mängelexemplar, X, 256 p. 14 illus. About this book: This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. The intended audience is senior undergraduates, graduate students, and researchers in either of those fields. 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.The logic used throughout the book is a higher-order one, since higher-order functions can have other functions as arguments and this capability can be exploited to provide abstractions for knowledge representation, methods for constructing predicates, and a foundation for logic-based computation. The book should be of interest to researchers in machine learning, especially those who study learning methods for structured data. Throughout, great emphasis is placed on learning comprehensible theories. The book serves as an introduction for computational logicians to machine learning, a particularly interesting and important application area of logic, and also provides a foundation for functional logic programming languages. Written for advanced students, researchers, scientists. Codice articolo 18644
Quantità: 1 disponibili
Foto dell'editore
Logic For Learning
Da: Swan Trading Company, GEORGETOWN, TX, U.S.A.
Valutazione del venditore 5 su 5 stelle
hardcover. Condizione: Good. Hardcover ex-library with typical marks shows moderate cover wear. Text is unmarked. Ships FAST! Codice articolo 2411200017
Quantità: 1 disponibili
Foto dell'editore
Logic For Learning
Da: Amazing Books Pittsburgh, Pittsburgh, PA, U.S.A.
Valutazione del venditore 5 su 5 stelle
hardcover. Condizione: Very Good. prev owners name on first page in pen. otherwise clean, sturdy, and unmarked - rw. Codice articolo Sq39502
Quantità: 1 disponibili
Immagini fornite dal venditore
Logic for Learning
Print on DemandDa: moluna, Greven, Germania
Valutazione del venditore 4 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book on learning and knowledge representation based on higher-order logic.This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those interested in computational logic, it. Codice articolo 4889573
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Logic for Learning
Editore:
Springer Berlin Heidelberg Aug 2003, 2003
ISBN 10: 3540420274
ISBN 13: 9783540420279
Nuovo
Rilegato
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. The intended audience is senior undergraduates, graduate students, and researchers in either of those fields. 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.The logic used throughout the book is a higher-order one, since higher-order functions can have other functions as arguments and this capability can be exploited to provide abstractions for knowledge representation, methods for constructing predicates, and a foundation for logic-based computation.The book should be of interest to researchers in machine learning, especially those who study learning methods for structured data. Throughout, great emphasis is placed on learning comprehensible theories. The book serves as an introduction for computational logicians to machine learning, a particularly interesting and important application area of logic, and also provides a foundation for functional logic programming languages. 272 pp. Englisch. Codice articolo 9783540420279
Quantità: 2 disponibili
Immagini fornite dal venditore
Logic for Learning - Cognitive Technologies - Learning Comprehensible Theories from Structured Data
Da: Literary Cat Books, Machynlleth, Powys, WALES, Regno Unito
Valutazione del venditore 4 su 5 stelle
Hardcover. Condizione: Near Fine. Condizione sovraccoperta: No Dust Jacket. (?); (?). This textbook presents 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. The book does not assume previous knowledge of either field. It is part of the Springer series Cognitive Technologies, which addresses subjects including natural-language processing, high-level computer vision, cognitive robotics, automated reasoning, and knowledge representation. ; 16x23.5x2cm; 267 pages. Codice articolo 64612
Quantità: 1 disponibili
Foto dell'editore
Logic for Learning: Learning Comprehensible Theories from Structured Data (Cognitive Technologies)
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9783540420279_new
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Logic for Learning : Learning Comprehensible Theories from Structured Data
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. The intended audience is senior undergraduates, graduate students, and researchers in either of those fields. 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. The logic used throughout the book is a higher-order one. Higher-order logic is already heavily used in some parts of computer science, for example, theoretical computer science, functional programming, and hardware verifica tion, mainly because of its great expressive power. Similar motivations apply here as well: higher-order functions can have other functions as arguments and this capability can be exploited to provide abstractions for knowledge representation, methods for constructing predicates, and a foundation for logic-based computation. The book should be of interest to researchers in machine learning, espe cially those who study learning methods for structured data. Machine learn ing applications are becoming increasingly concerned with applications for which the individuals that are the subject of learning have complex struc ture. Typical applications include text learning for the World Wide Web and bioinformatics. Traditional methods for such applications usually involve the extraction of features to reduce the problem to one of attribute-value learning. Codice articolo 9783540420279
Quantità: 1 disponibili
Immagini fornite dal venditore
Logic for Learning
ISBN 10: 3540420274
ISBN 13: 9783540420279
Nuovo
Rilegato
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. Neuware -This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. The intended audience is senior undergraduates, graduate students, and researchers in either of those fields. 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. The logic used throughout the book is a higher-order one. Higher-order logic is already heavily used in some parts of computer science, for example, theoretical computer science, functional programming, and hardware verifica tion, mainly because of its great expressive power. Similar motivations apply here as well: higher-order functions can have other functions as arguments and this capability can be exploited to provide abstractions for knowledge representation, methods for constructing predicates, and a foundation for logic-based computation. The book should be of interest to researchers in machine learning, espe cially those who study learning methods for structured data. Machine learn ing applications are becoming increasingly concerned with applications for which the individuals that are the subject of learning have complex struc ture. Typical applications include text learning for the World Wide Web and bioinformatics. Traditional methods for such applications usually involve the extraction of features to reduce the problem to one of attribute-value learning.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch. Codice articolo 9783540420279
Quantità: 2 disponibili