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Exploring New Generative Art Schemes: A Practice-based Approach, Slides of Robotics

An overview of various generative art schemes and their implementation using genetic algorithms. It covers the ubiquity of ga schemes, standard search paradigms, and non-interactive algorithms. The document also introduces a practice-based approach for exploring new generative art schemes and concludes with considerations for image assessment parameters and fitness function taxonomy.

Typology: Slides

2013/2014

Uploaded on 01/29/2014

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A Practice-based Approach for
Exploring New Generative Art
Schemes
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A Practice-based Approach for

Exploring New Generative Art

Schemes

Outline

 The ubiquity of GA schemes  Standard search paradigm  Non-interactive genetic algorithms  Our practice-based approach  Conclusions

  •  Biomorphs – Dawkins ’
  •  Evolving Expressions – Sims ’
  •  Mutator - Todd & Latham ’
  •  Fractals – Sprott ’
  •  Strange Attractors – Krawczyk ’
  •  Polynomiography – Kalantari ’
  •  Self-similar Tilings – Priebe ’
  •  Spiral Tilings – Palmer ’
  •  Hyperbolic Spirals – Dunham ’
  •  Bar Grids – Roelofs ’
  •  Spirolaterals – Krawczyk ’
  •  Component Sculptures – Hart ’
  •  Fermat Spirals – Krawczyk ’
  •  TSP Art – Galanter ’

 TSP Art – Kaplan & Bosch ’  Polar Transformations – Bleicher ’  Reaction Diffusion – Behravan & Carlisle ’  ACO – Aupetit et al ’  Cellular Morphognesis – Eggenberger ’

Evolving Expressions IGA

(Greenfield ’92-’96)

 Modeled after Sims  User interface to control genetics  Features

  • Node iteration
  • External image acquisition
  • Palette management
  • 2D and 3D imaging

Slippage I-III

Expressionism IV

Re-coloring Example

A

A fitness function taxonomy

 Positive Feedback

  • simulated co-evolution
  • neural nets (Cardoso et al ’98)  Negative Feedback
  • simulated immune systems (Romero et al ’05)
  • simulated diseases (Dorin ’05)  Direct Control
  • user-designed  Indirect Control
  • multi-objective optimization
  • ant colony optimization  Learning
  • image analogies (Hertzmann et al ’01)
  • simulated gaze data

Our practice-based approach

 Co-evolutionary framework (’00)  Color segmentation analysis (’02)  Multi-objective Optimization (’03)  Virtual ant paintings (’05)  Cellular morphogenesis (’05)  Serial polar transf. motifs (’05)