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Interactively Evolved Art

All art below was generated by interactive art evolution programs incorporated into MM-NEAT, a software package that evolves artificial neural networks. Each piece of art presented below was generated by a special type of neural network known as a Compositional Pattern Producing Network (CPPN). Specifically, human subjects used interactive evolution to select the art they enjoyed the most, resulting in the generation of more art in line with their preferences. Although the larger MM-NEAT project still retains the ability to evolve such artifacts, a simplified version of the code that focuses exclusively on interactive evolution with CPPNs is also available at https://github.com/schrum2/CPPNArtEvolution. This code was written by Isabel Tweraser and Lauren Gillespie as part of Southwestern University's SCOPE summer research program.

Art Selected By Human Subjects

Selecting the name of one of the art generation programs on the left will provide you with a list of individuals that participated in a human subject study to understand the capabilities of these systems. Users were either exposed to both Picbreeder and AnimationBreeder, or 3DObjectBreeder and 3DAnimationBreeder. Therefore, subject ID numbers for the two 2D art programs correspond to the same person, and subject ID numbers for the two 3D art programs also correspond to the same person (for a total of 40 participants). Therefore, you can compare what one individual generated with one program to what that same individual generated with another program. However, no subject used both 2D and 3D art programs. Users interacted with each program for 15 generations. In each generation, 20 options were available to select from, but only the items that each user actually selected are accessible in the interface below. Images and animations are reduced in size for the sake of space, but the original CPPNs can represent the art depicted here at arbitrarily large resolutions.
Picbreeder
AnimationBreeder
3DObjectBreeder
3DAnimationBreeder

Movies


Picbreeder

This remake of Picbreeder allows a single user to evolve artistic images using Compositional Pattern Producing Networks, just like the original. However, the interface has some extra features offering more control over the process.

AnimationBreeder

The AnimationBreeder adds a time input to the evolved Compositional Pattern Producing Networks so that multiple images like those produced by Picbreeder can be produced by a single CPPN as a function of time.

3DObjectBreeder

The 3DObjectBreeder uses Compositional Pattern Producing Networks to evolve 3D shapes using the same interface as Picbreeder and AnimationBreeder. This program is a remake of EndlessForms, though it does not use the Marching Cubes algorithm to smooth out the evolved shapes. However, it does allow the color of each voxel to be evolved, and also allows for slight displacements in the location of each voxel so that strict adherence to a grid of voxels is not required.

3DAnimationBreeder

The 3DAnimationBreeder adds a time input to the Compositional Pattern Producing Networks from 3DObjectBreeder in order to animate the 3D shapes that are formed. The presence, color, and displacement of voxels can change over time.

Associated Publications


Peer-Reviewed Conference Publications


Dagstuhl Reports


Undergraduate Poster Presentations Supervised


Associated Movies and Images


Miscellaneous Content

  • Summer 2022: Generating Structures with AI in Minecraft: SCOPE Research Presentation made by my SCOPE Summer research students to present to other SCOPE students
  • Summer 2021: Quality Diversity and Creative Divergent Search: SCOPE Research Presentation made by my SCOPE Summer research students to present to other SCOPE students
  • Spring 2021: Computers and Creativity: An article about my former student Anna Krolikowski which references me and our work on Zentangles
  • Spring 2021: Generating Art: An article about my former student Sarah Friday which references me and our work on Zentangles
  • Spring 2019: Patience, Grit, and an Open Mind: An article about my former student Lauren Gillespie which references me and our work on both Tetris and AnimationBreeder
  • Spring 2019: Infinite Art Gallery: A Game World of Interactively Evolved Artwork, presentation by Bryan Hollingsworth at the Southwestern University Undergraduate Research & Creative Works Symposium
  • Fall 2018: Musician Presents Research at International Computer Science Conference: An article about my former student Isabel Tweraser which references me and our work on AnimationBreeder
  • Fall 2018: The cover of SIGEVOlution Volume 11, Issue 4 features art generated by AnimationBreeder, the interactive evolution system described in a GECCO 2018 paper co-authored with SU students. SIGEVO is the ACM Special Interest Group on Genetic and Evolutionary Computation.
  • Fall 2018: Evolutionary Computation Applied to Digital Entertainment and the Arts, poster presented at the President's Appreciation Celebration for Southwestern University donors.
  • Summer 2018: Neuroevolution in Video Games: "Mad Science Monday" presentation made by my SCOPE Summer research students to present to other SCOPE students
  • Spring 2018: Querying Across Time to Interactively Evolve Animations, presentation by Isabel Tweraser at the Southwestern University Undergraduate Research & Creative Works Symposium
  • Fall 2017: Creating Art Through Function Composition: presented to Southwestern University students as a 107 Lecture.
  • Summer 2017: Evolutionary Computation for Creativity and Intelligence: "Mad Science Monday" presentation made by my SCOPE Summer research students to present to other SCOPE students
  • Summer 2016: Evolutionary Computation for Creativity and Intelligence: "Mad Science Monday" presentation made by my SCOPE Summer research students to present to other SCOPE students

  • Last Updated: 5/28/2019