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Evolution of Artificial Neural Development : In search of learning genes

Author: Gul Muhammad Khan
Publisher: Cham : Springer International Publishing : Imprint : Springer, 2018.
Series: Studies in computational intelligence, 725.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Gul Muhammad Khan
ISBN: 9783319674667 3319674668 9783319674643 3319674641
OCLC Number: 1021260443
Description: 1 online resource (XIII, 139 pages 55 illustrations, 28 illustrations in color.) : online resource.
Contents: Making the Computer 'Brained' --
The Biology of Brain:An insight into the Human Brain --
Evolutionary Computation --
Artificial Neural Network (ANNs) --
Structure and Operation of Cartesian Genetic Programming Developmental Network (CGPDN) Model --
Wumpus World --
Checkers --
Concluding Remarks and Future Directions.
Series Title: Studies in computational intelligence, 725.
Responsibility: by Gul Muhammad Khan.

Abstract:

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". The book will be of interest not only to the specialized scientific community pursuing machine intelligence, but also general readers who would like to know more about the incorporation of intelligent behaviour in machines, inspired by the human brain.

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