Neuro-Evolution Using Recombinational Algorithms and Embryogenesis for Robotic Control

Neuro-Evolution Using Recombinational Algorithms and Embryogenesis for Robotic Control

Control tasks involving dramatic nonlinearities, such as decision making, can be challenging for classical design methods. However, autonomous, stochastic design methods such as evolutionary computation have proved effective. In particular, genetic algorithms that create designs via the application...

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Bibliographic Details
Main Author: Roy, Anthony Mathew
Format: Others
Published: 2010
Online Access:https://thesis.library.caltech.edu/5944/1/main.pdf
Roy, Anthony Mathew (2010) Neuro-Evolution Using Recombinational Algorithms and Embryogenesis for Robotic Control. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/YNED-VN66. https://resolver.caltech.edu/CaltechTHESIS:06092010-140839602 <https://resolver.caltech.edu/CaltechTHESIS:06092010-140839602>

Internet

https://thesis.library.caltech.edu/5944/1/main.pdf
Roy, Anthony Mathew (2010) Neuro-Evolution Using Recombinational Algorithms and Embryogenesis for Robotic Control. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/YNED-VN66. https://resolver.caltech.edu/CaltechTHESIS:06092010-140839602 <https://resolver.caltech.edu/CaltechTHESIS:06092010-140839602>

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