Evolution and Dynamics

Part of the IFSR International Series on Systems Science and Engineering book series (IFSR, volume 11)


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.


Genetic Algorithm Fitness Function Genetic Drift Strange Attractor Iterate Function System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Plenum Press, New York 1997

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