Advances in the evolutionary synthesis of intelligent agents

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Bibliographic Details
Main Author Patel, Mukesh
Other Authors Honavar, Vasant, Balakrishnan, Karthik, 1970-
Format Electronic eBook
LanguageEnglish
Published Cambridge, Mass. : MIT Press, 2001.
SeriesBradford book.
Subjects
Online AccessFull text
ISBN9780262281300
Physical Description1 online zdroj (xxiv, 480 pages) : illustrations

Cover

Table of Contents:
  • 1. Evolutionary and neural synthesis of intelligent agents / by Karthik Balakrishnan and Vasant Honavar
  • 2. Cellular encoding for interactive evolutionary robotics / by Frâedâeric 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. Morâan
  • 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 Mčuhlenbein and Thilo Mahnig.