Abstract
In this chapter we will return to the genetic algorithm, which was introduced in Chapter One. The relevance of the genetic algorithm to the psynet model has already been established—GA’s, it seems, are an abstract, archetypal model of a certain type of psychological creativity. Here we will be concerned with genetic algorithms as dynamical systems, and with the use of genetic algorithms to evolve other dynamical systems. Rather than merely cranking out genetic-algorithm applications, the focus is on understanding what the genetic algorithm is, what it can do, and why it is relevant to human and computer creativity.
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© 1997 Plenum Press, New York
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(1997). Evolution and Dynamics. In: From Complexity to Creativity. IFSR International Series on Systems Science and Engineering, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-0-585-34713-4_6
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DOI: https://doi.org/10.1007/978-0-585-34713-4_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-306-45518-6
Online ISBN: 978-0-585-34713-4
eBook Packages: Springer Book Archive