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Evolution of Complexity and Neural Topologies

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Guided Self-Organization: Inception

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 9))

Abstract

One of the grandest and most intriguing self-organizing systems is nature itself. Whether couched in terms of evolutionary theory (Darwin 1859), information theory (Avery 2003), or thermodynamics and maximum physical entropy (Jaynes 1957a,b; Swenson 1989) natural processes have yielded a remarkable diversity of behavioral and organizational levels of complexity ranging from microbes to man.

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  1. School of Informatics & Computing, Indiana University, 919 E. 10th St., Bloomington, Indiana, 47408, USA

    Larry S. Yaeger

  2. Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA, 94043, USA

    Larry S. Yaeger

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  1. CSIRO ICT Centre, Epping, Australia

    Mikhail Prokopenko

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Yaeger, L.S. (2014). Evolution of Complexity and Neural Topologies. In: Prokopenko, M. (eds) Guided Self-Organization: Inception. Emergence, Complexity and Computation, vol 9. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53734-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-53734-9_15

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