Evolution of Artificial Neural Development In search of learning genes
Language: English
Published by Palgrave Macmillan, 2017
Series: Book 254 of 538 - Studies in Computational Intelligence
- Hardcover
- New
Condition: New
US$ 151.82
Quantity: 2 available
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Presents recent research on the evolution of artificial neural developmentSearches for learning genesWritten by leading experts in the field Sprache: Englisch Gewicht in Gramm: 354.
Seller Inventory # IB-711561
- Title
- Evolution of Artificial Neural Development In search of learning genes
- Author
- Gul Muhammad Khan
- Publisher
- Palgrave Macmillan
- Publication year
- 2017
- Condition
- Neu
- Binding
- Gebundene Ausgabe
- Language
- English
- ISBN 10
- 3319674641
- ISBN 13
- 9783319674643
- Item weight
- 354 grams
- Series
- Book 254 of 538: Studies in Computational Intelligence
This book presents recent research on the evolution of artificial neural development, and searches for learning genes. It is fascinating to see how all biological cells share virtually the same traits, but humans have a decided edge over other species when it comes to intelligence. Although DNA decides the form each particular species takes, does it also account for intelligent behaviour in living beings?
The authors explore the factors that are perceived as intelligent behaviour in living beings and the incorporation of these factors in machines using genetic programming, which ultimately provides a platform for exploring the possibility of machines that can learn by themselves, i.e. that can “learn how to learn”.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book presents recent research on the evolution of artificial neural development, and searches for learning genes. It is fascinating to see how all biological cells share virtually the same traits, but humans have a decided edge over other species when it comes to intelligence. Although DNA decides the form each particular species takes, does it also account for intelligent behaviour in living beings?
The authors explore the factors that are perceived as intelligent behaviour in living beings and the incorporation of these factors in machines using genetic programming, which ultimately provides a platform for exploring the possibility of machines that can learn by themselves, i.e. that can “learn how to learn”.
"About the title" may belong to another edition of this title.
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