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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.
- Sales Rank: #2123040 in Books
- Published on: 2004-01-30
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .75" w x 7.00" l, 1.18 pounds
- Binding: Paperback
- 332 pages
Review
This is an exciting new area that has implications and ramifications ranging from psychology to artificial life; can we create robots with intelligent or adaptive behavior using techniques comparable to the Darwinian evolution that created the animals and ourselves? Here is an authoritative, clearly written survey written by two of the researchers who helped to pioneer the field.
(Inman Harvey, Centre for Computational Neuroscience and Robotics and Centre for the Study fo Evolution, University of Sussex)An excellent book providing a thorough coverage of the subject. Clearly and insightfully written, this is a must for researchers and postgraduate students interested in new approaches to intelligent robotics.
(Phil Husbands, School of Cognitive and Computing Sciences, University of Sussex) About the Author
Stefano Nolfi is research director at the Institute of Cognitive Science and Tecnology and head of the Laboratory of Artificial Life and Robotics. He coordinated the European project ECAgents (Embodied and Communicating Agents) and is team leader of the European Projects I-TALK (Transfer of Action and Language Knowledge in Robots) and Swarmanoid (Towards Humanoid Robotic Swarms Humanoids).
Dario Floreano is Director of the Laboratory of Intelligent Systems at the Swiss Federal Institute of Technology in Lausanne (EPFL). He is the coauthor of Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines (MIT Press, 2000).
Most helpful customer reviews
14 of 15 people found the following review helpful.
Really great stuff
By A Customer
This is a not too technical book, introducing you to evolutionary robotics. It covers a lot of interesting work done in the field over the last few years.
Using genetic algorithms it is possible to construct the brain of a robot ( Neural network ), and even (though harder) the hardware itself. The book gives an introduction to genetic algortihms & artificial neural networks, but the reader should still be somewhat familiar with these concepts before buying this book.
After reading this book, I did one of the experiments mentioned in the book. While I only did this with a freeware Kephara robot simulator, it was still fun.
2 of 4 people found the following review helpful.
Really great stuff
By A Customer
This is a not too technical book, introducing you to evolutionary robotics. It covers a lot of interesting work done in the field over the last few years.
Using genetic algorithms it is possible to construct the brain of a robot ( Neural network ), and even (though harder) the hardware itself. The book gives an introduction to genetic algortihms & artificial neural networks, but the reader should still be somewhat familiar with these concepts before buying this book.
After reading this book, I did one of the experiments mentioned in the book. While I only did this with a freeware Kephara robot simulator, it was still fun.
0 of 0 people found the following review helpful.
Informative!
By kc-lam
The behavior of passive robots depend upon the choice of its designer and it can hardly be said to be autonomous. In contrast, evolutionary robotics largely rely on self organization and many of the evolved robots exploit active interaction with the environment.
In artificial evolution of robots, importance is usually given to autonomous interaction with the physical environment. In addition, learning can enhance the adaptive power of evolution. One way to avoid the problem of time is to evolve robots in simulation and then run the most successful individuals on the physical robot. However, in order to generate identical behaviors in the real environment, the robot-environment interactions should be accurately modeled in the simulator.
With illustrations by experiments, this book provides a useful introduction to evolutionary robotics. It presents how to evolve robots and explore competitive co-evolution and evolvable hardware.
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