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Advances in the evolutionary synthesis of intelligent agents

Author: Mukesh Patel; Vasant Honavar; Karthik Balakrishnan
Publisher: Cambridge, Mass. : MIT Press, 2001.
Series: Bradford book.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"This book explores a central issue in artificial intelligence, cognitive science, and artificial life: how to design information structures and processes that create and adapt intelligent agents through evolution and learning." "The book is organized around four topics: the power of evolution to determine effective solutions to complex tasks, mechanisms to make evolutionary design scalable, the use of evolutionary  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Patel, Mukesh.
Advances in the evolutionary synthesis of intelligent agents.
Cambridge, Mass. : MIT Press, 2001
(DLC) 00053691
(OCoLC)45315232
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Mukesh Patel; Vasant Honavar; Karthik Balakrishnan
ISBN: 0585387168 9780585387161 9780262162012 0262162016 0262281309 9780262281300
OCLC Number: 49569598
Language Note: English.
Notes: "A Bradford book."
Description: 1 online resource (xxiv, 480 pages) : illustrations
Contents: 1. Evolutionary and neural synthesis of intelligent agents / by Karthik Balakrishnan and Vasant Honavar --
2. Cellular encoding for interactive evolutionary robotics / by Frédéric Gruau and Kameel Quatramaran --
3. The emergence of communication through synthetic evolution / by Bruce J. MacLennan --
4. Optimization of classifiers using genetic algorithms / by J.J. Merelo, A. Prieto and F. Morán --
5. Evolving neuro-controllers and sensors for artificial agents / by Karthik Balakrishnan and Vasant Honavar --
6. Combined biological metaphors / by Egbert J.W. Boers and Ida G. Sprinkhuizen-Kuyper --
7. Evolutionary neurogenesis applied to mobile robotics / by Oliver Michel --
8. Development in neural networks / by Domenico Parisi and Stefano Nolfi --
9. Evolution and learning in radial basis function neural networks : a hybrid approach / by Brian Carse, Terence C. Fogarty and John C.W. Sullivan --
10. Co-evolution and ontogenetic change in competing robots / by Dario Floreano, Stefano Nolfi and Francesco Mondada --
11. Goal directed adaptive behavior in second-order neural networks : learning and evolving in the MAXSON architecture / by Federick L. Crabbe and Michael G. Dyer --
12. Evolving heterogeneous neural agents by local selection / by Filippo Menczer, W. Nick Street and Melania Degeratu --
13. Learning sequential decision tasks through symbiotic evolution of neural networks / by David E. Moriarty and Risto Miikkulainen --
14. From evolving a single neural network to evolving neural network ensembles / by Xin Yao and Yong Liu --
15. Evolutionary synthesis of Bayesian networks for optimization / by Heinz Mühlenbein and Thilo Mahnig.
Series Title: Bradford book.
Responsibility: edited by Mukesh Patel, Vasant Honavar, Karthik Balakrishnan.
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Abstract:

This book explores a central issue in artificial intelligence, cognitive science, and artificial life: how to design information structures and processes that create and adapt intelligent agents  Read more...

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"This book collects papers on the most interesting ongoing research on evolutionary approaches to the development of artificial neural networks. It will prove extremely valuable for researchers and Read more...

 
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