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Genetic Programming and Evolvable Machines

, Volume 11, Issue 3–4, pp 441–443 | Cite as

Dario Floreano and Claudio Mattiussi (eds): Bio-inspired artificial intelligence: theories, methods, and technologies

  • Ivan Garibay
Book Review

Traditionally artificial intelligence has been focused on attempting to replicate the cognitive abilities of the human brain. Alternative approaches to artificial intelligence take inspiration from a wider range of biological processes such as evolution, networks of neurons and learning. In recent decades there has been an explosion of new artificial intelligence methods inspired by even more biological processes, such as the immune system, colonies of ants, physical embodiment, development, coevolution, self-organization, and behavioral autonomy, to mention just a few.

“Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies”, by Dario Floreano and Claudio Mattiussi, is a systematic and comprehensive introduction to the emerging field that groups all these methods: biologically inspired artificial intelligence. As a result, it discusses biological and artificial systems that operate at a wide range of time and space scales, but manages to move fluently from slow...

References

  1. 1.
    T. Dobzhansky, Nothing in biology makes sense except in the light of evolution. Am. Biol. Teach. 35, 125–129 (1973)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.University of Central FloridaOrlandoUSA

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