Neural-Symbolic Learning Systems: Foundations and Applications (Perspectives in Neural Computing) - Softcover
Synopsis
Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence.
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.
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Neural-Symbolic Learning Systems: Foundations and Applications (Perspectives in Neural Computing)
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Neural-Symbolic Learning Systems: Foundations And Applications (Perspectives in Neural Computing)
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 288 | Sprache: Englisch | Produktart: Bücher | Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. 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. Seller Inventory # 1046486/202
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Neural-Symbolic Learning Systems
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ISBN 10: 1852335122
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. 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. 288 pp. Englisch. Seller Inventory # 9781852335120
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Neural-Symbolic Learning Systems
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides the first single-source introduction to the field of knowledge-based neuro-computingIncludes real-world applications of neural-symbolic integration systemsArtificial Intelligence is concerned with producing devices that help or replace huma. Seller Inventory # 4289603
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Neural-Symbolic Learning Systems | Foundations and Applications
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Taschenbuch. Condition: Neu. Neural-Symbolic Learning Systems | Foundations and Applications | Artur S. D'Avila Garcez (u. a.) | Taschenbuch | Perspectives in Neural Computing | xiv | Englisch | 2002 | Springer | EAN 9781852335120 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 103495086
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Neural-Symbolic Learning Systems: Foundations and Applications
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ISBN 10: 1852335122
ISBN 13: 9781852335120
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Neural-Symbolic Learning Systems
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computing Science and Artificial Intelligence are concerned with producing devices that help and/or replace human beings in their daily activities. To be successful, adequate modelling of these activities needs to be carried out and this has accelerated the development of both old and new disciplines, including Logic and Computation, Neural Networks, Genetic Algorithms and Probabilistic/Casual Networks. This book looks at how these techniques could complement each other and how, by understanding the role of each in a particular application, we can pave the way towards the development of more effective intelligent systems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 288 pp. Englisch. Seller Inventory # 9781852335120