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Neural-symbolic Learning Systems
Garcez, Artur S.D'Avilla; Broda, Krysia B.; Gabbay, Dov M.
€ 197.17
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Description for Neural-symbolic Learning Systems
Paperback. Computing Science and Artificial Intelligence are concerned with producing devices that help and/or replace human beings in their daily activities. This work looks at how techniques could complement each other and how we can pave the way towards the development of more effective intelligent systems. Series: Perspectives in Neural Computing. Num Pages: 271 pages, 30 black & white illustrations, biography. BIC Classification: UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate; (XV) Technical / Manuals. Dimension: 234 x 156 x 15. Weight in Grams: 413.
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 ... Read more
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 ... Read more
Product Details
Format
Paperback
Publication date
2002
Publisher
Springer London Ltd United Kingdom
Number of pages
271
Condition
New
Series
Perspectives in Neural Computing
Number of Pages
271
Place of Publication
England, United Kingdom
ISBN
9781852335120
SKU
V9781852335120
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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