Bio-Inspired Self-Organizing Robotic Systems

Bio-Inspired Self-Organizing Robotic Systems

Self-organizing approaches inspired from biological systems, such as social insects, genetic, molecular and cellular systems under morphogenesis, and human mental development, has enjoyed great success in advanced robotic systems that need to work in dynamic and changing environments.  Compared with...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Meng, Yan (Editor), Jin, Yaochu (Editor)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Series:Studies in Computational Intelligence, 355
Subjects:
Engineering.
Artificial intelligence.
Computational intelligence.
Robotics.
Automation.
Computational Intelligence.
Robotics and Automation.
Artificial Intelligence (incl. Robotics).
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