Evolutionary Art

1
Evolutionary Art

• (What we did on our holidays)
• David Broadhurst
• Dan Costelloe
• Lynne Jones
• Pantelis Nasikas
• Joanne Walker

2
Introduction

• Project aims
• Develop some nice art
• Use Genetic Algorithms to evolve art
• Analyse the human-computer interface

3
Our Tools

• Graphical User Interface written in java
• Genetic Algorithm Engine
• Evolvable .gif images

4
Objectives

• Primary objective nice art
• Secondary objective modify GA engine

5
Art Requirements

• Needs to be simple yet attractive
• Evolvable through parameters
• Written in simple java for easy integration

6
Art Used

• Kaleidoscope applet
• Simple shapes bright colours
• Use of reflections and symmetry add interest
• Animation gives extra dimension
• Small simple java applet
• (Demo)

7
Chromosome Design

• Existing code used integer array
• Our parameters
• Shape type (line / rectangle / circle / mix)
• Colour of shapes (10 x 255 colour palette)
• Background colour
• Symmetry style (horizontal / vertical / diagonal
  / mix)

8
Experimentation

• Considered mutation rate and crossover type
• Attempted to evolve a population of solutions
  without circles
• Recorded speed of convergence

9
Mutation

• Guassian mutation
• Probability varied between 0 and 1
• As rate increased more generations were required
• Convergence of other parameters increased as
  mutation rate decreased

10
Crossover

• Considered three types
• Single point
• Random N point
• Uniform
• Similar results obtained for each

11
Demo
12
Human Computer Interface

• Current layout is easy to use
• Can be time consuming after a few generations
• Tournament style selection may be an improvement

13
Conclusions

• Future work
• Implement other evolutionary algorithms
• Addition of visual effects on the animations
• Revision of Human Machine Interface

14
Thanks to.

• Ben
• Gusz
• Bart (dude)
• Andrew