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Evolutionary and Swarm Design in Science, Art, and Music

  • Christian Jacob
  • Gerald Hushlak
Part of the Natural Computing Series book series (NCS)

Summary

Evolutionary Design Evolutionary design can take many forms. In this chapter, we describe how different evolutionary techniques — such as genetic programming and evolution strategies — can be applied to a wide variety of nature-inspired designs. We will show how techniques of interactive evolutionary breeding can facilitate the creative processes of design. As practical examples we demonstrate how to use implicit surface modeling to create virtual sculptures, and furniture designs through evolutionary breeding.

Rather than creating variations of blueprints through an evolutionary process, we then focus on the evolution of ‘design programs’. That is, instead of a static description (blueprint) of an object, we evolve recipes or algorithms to build objects. This leads to a much wider repertoire of variability on the designer’s side and can be implemented in a straightforward manner using genetic programming. Starting with a simple breeding approach of fractals, we give examples of how to — either automatically or interactively — evolve growth programs for plants with particular characteristics, which we illustrate using a garden of artificial flowers. We use evolvable Lindenmayer systems (L-systems) to capture growth processes.

The evolution of choreographic swarm interactions leads to new ways of ‘swarm programming’, where changes in control parameters result in emergent agent behaviours. Swarm grammars, as we will show, combine swarming agents with developmental programs as an extension of L-systems. We demonstrate how to use this technique to generate virtual paintings on 2D and 3D canvases. These SwarmArt implementations have also been exhibited in various museums as interactive computer installations, which we will use to describe how to integrate music and sound generation into evolutionary swarm systems.

Keywords

Swarm Intelligence Implicit Surface Evolutionary Design Replacement Rule Evolutionary Design 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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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Christian Jacob
    • 1
    • 2
  • Gerald Hushlak
    • 3
  1. 1.Department of Computer ScienceUniversity of CalgaryCanada
  2. 2.Department of Biochemistry&Molecular BiologyUniversity of CalgaryCanada
  3. 3.Department of ArtUniversity of CalgaryCanada

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