Authors:
- Provides the first single-source introduction to the field of knowledge-based neuro-computing
- Includes real-world applications of neural-symbolic integration systems
- Includes supplementary material: sn.pub/extras
Part of the book series: Perspectives in Neural Computing (PERSPECT.NEURAL)
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Table of contents (9 chapters)
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Front Matter
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Introduction and Overview
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Knowledge Refinement in Neural Networks
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Front Matter
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Knowledge Extraction from Neural Networks
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Front Matter
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Knowledge Revision in Neural Networks
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Front Matter
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Back Matter
About this book
This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications.
Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.
Authors and Affiliations
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Department of Computing, City University, London
Artur S. d’Avila Garcez
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Department of Computing, Imperial College, London
Krysia B. Broda
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Department of Computer Science, King’s College, London
Dov M. Gabbay
Bibliographic Information
Book Title: Neural-Symbolic Learning Systems
Book Subtitle: Foundations and Applications
Authors: Artur S. d’Avila Garcez, Krysia B. Broda, Dov M. Gabbay
Series Title: Perspectives in Neural Computing
DOI: https://doi.org/10.1007/978-1-4471-0211-3
Publisher: Springer London
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London 2002
Softcover ISBN: 978-1-85233-512-0Published: 06 August 2002
eBook ISBN: 978-1-4471-0211-3Published: 06 December 2012
Series ISSN: 1431-6854
Edition Number: 1
Number of Pages: XIV, 271
Number of Illustrations: 30 b/w illustrations
Topics: Artificial Intelligence, Information Systems and Communication Service, Communications Engineering, Networks