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

by Stefano Nolfi, Dario Floreano

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.

Genres: Science

384 pages, Hardcover

First published January 1, 2000

Reviews

[Aadesh · Rating 4 out of 5]

It was good but since it was published way back on 2000 lots of things have changed.

[Miguel Duarte · Rating 5 out of 5]

"Evolutionary Robotics" by Dario Floreano and Stefano Nolfi presents a thorough analysis of the most relevant work in this field up the the time of publishing (2000). It also provides an excellent overview and description of the processes involved in the development of evolutionary methodologies, particularly those which involve robotics or simulations of embodied agents.
The approach of self-organization of behavior clearly has many advantages over traditional hand-crafted solutions. I found it a great introduction to this huge world, with many examples of how to design and conduct successful experiments. I was surprised with the sheer scope of possibilities that can be explored and investigated, from reactive architectures, to co-evolution, learning during lifetime, and changing morphologies.
This book is definitely a primer and should be read by anyone that has even a remote interest in the field of Machine Learning and Robotics.

[Alpseu]

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[Simon Hutchinson · Rating 4 out of 5]

An interesting and thorough overview of the subject.