Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines

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Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines

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內容描述

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Description:

Evolutionary robotics
is a new technique for the automatic creation of autonomous robots. Inspired
by the Darwinian principle of selective reproduction of the fittest, it views
robots as autonomous artificial organisms that develop their own skills in
close interaction with the environment and without human intervention. Drawing
heavily on biology and ethology, it uses the tools of neural networks, genetic
algorithms, dynamic systems, and biomorphic engineering. The resulting robots
share with simple biological systems the characteristics of robustness,
simplicity, small size, flexibility, and modularity.In evolutionary
robotics, an initial population of artificial chromosomes, each encoding the
control system of a robot, is randomly created and put into the environment.
Each robot is then free to act (move, look around, manipulate) according to
its genetically specified controller while its performance on various tasks is
automatically evaluated. The fittest robots then "reproduce" by swapping parts
of their genetic material with small random mutations. The process is repeated
until the "birth" of a robot that satisfies the performance
criteria.This book describes the basic concepts and methodologies of
evolutionary robotics and the results achieved so far. An important feature is
the clear presentation of a set of empirical experiments of increasing
complexity. Software with a graphic interface, freely available on a Web page,
will allow the reader to replicate and vary (in simulation and on real robots)
most of the experiments.Dario Floreano is Professor of Evolutionary
and Adaptive Systems at the Swiss Federal Institute of Technology.

 
Table of
Contents:

Acknowledgments
ix

Preface
xi

1
The
role of self-organization for the synthesis and the understanding of
behavioral systems
1

2
Evolutionary and neural techniques
19

3
How to
evolve robots
49

4
Evolution of simple navigation
69

5
Power
and limits of reactive intelligence
93

6
Beyond
reactive intelligence
121

7
Learning and evolution
153

8
Competitive co-evolution
189

9
Encoding, mapping, and development
223

10
Complex hardware morphologies: Walking machines
241

11
Evolvable hardware
261

Conclusions
277

Notes
281

References
295

Index
317

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