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Mechanisms for Complex Systems Engineering Through Artificial Development

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Morphogenetic Engineering

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

We argue that artificial development is an appropriate means of approaching complex systems engineering. Artificial development works via the inclusion of mechanisms that enhance the evolvability of a design space. Two of these mechanisms, regularities and adaptive feedback with the environment, are discussed. We concentrate on the less explored of the two: adaptive feedback. A concrete example is presented and applied to a simple artificial problem resembling vasculogenesis. It is shown that the use of a local feedback function substantively improves the efficacy of a machine learner on the problem. Further, inclusion of this adaptive feedback eliminates the sensitivity of the machine learner to a system parameter previously shown to correspond to problem hardness.

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Notes

  1. 1.

    One proposed definition from Lipson defines “structural regularities” as an “inverse Kolmogorov complexity”, that is, the amount by which a structural description could be compressed by a Universal Turing Machine [26]. Unfortunately, Kolmogorov complexity is generally uncomputable, and simpler forms of compression are often poorly correlated [20]. Further, the attempt to approximate the Kolmogorov complexity of evolved designs does not figure largely in current AD literature. Thus, we believe that most authors are referencing something quite different from Lipson’s definition when discussing “regularities”.

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Acknowledgments

TK and WB would like to thank Nature for billions of years of tireless effort. Smashing stuff! In addition, NSERC of Canada supported WB by Discovery Grant RGPIN 283304-07.

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Authors and Affiliations

  1. Complex Systems Institute - Paris Ile-de-France (ISC-PIF), CNRS, 57-59 rue Lhomond, 75005, Paris, France

    Taras Kowaliw

  2. Department of Computer Science, Memorial University, St. John’s, Newfoundland, A1B 3X5, Canada

    Wolfgang Banzhaf

Authors
  1. Taras Kowaliw
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  2. Wolfgang Banzhaf
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Correspondence to Taras Kowaliw .

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Editors and Affiliations

  1. Institut des Systèmes Complexes, Paris Ile-de-France, Ecole Polytechnique, rue Lhomond 57-59, Paris, 75005, France

    René Doursat

  2. Binghamton University, Dept. Bioengineering, State University of New York, Binghamton, 13902-6000, New York, USA

    Hiroki Sayama

  3. Faculté des Sciences et Technologie, Lab. LACL-EA 4219, Université Paris-Est Créteil, avenue due Général de Gaulle 61, Créteil Cedex, 94010, France

    Olivier Michel

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Kowaliw, T., Banzhaf, W. (2012). Mechanisms for Complex Systems Engineering Through Artificial Development. In: Doursat, R., Sayama, H., Michel, O. (eds) Morphogenetic Engineering. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33902-8_13

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  • DOI: https://doi.org/10.1007/978-3-642-33902-8_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33901-1

  • Online ISBN: 978-3-642-33902-8

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