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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
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Picbreeder: a case study in collaborative evolutionary exploration of design space.

Jimmy Secretan1, Nicholas Beato, David B D'Ambrosio

  • 1Department of Electrical Engineering and Computer Science, University of Central Florida, USA. secretj@gmail.com

Evolutionary Computation
|October 23, 2010
PubMed
Summary

Collaborative interactive evolution (CIE) using Picbreeder enhances artifact generation by combining multiple user feedback. This approach fosters proliferation of complex, evolved images unlike other systems.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Interactive evolutionary computation (IEC) is suitable for subjective or complex fitness domains.
  • Collaborative feedback from multiple users may enhance artifact generation quality and quantity.
  • Existing IEC systems lack mechanisms for large-scale collaborative evolution and image proliferation.

Purpose of the Study:

  • To explore the potential of collaborative interactive evolution (CIE) in improving generated artifacts.
  • To introduce and analyze the Picbreeder system as a large-scale online experiment in CIE.
  • To identify strengths, challenges, and lessons learned for future CIE system design.

Main Methods:

  • Picbreeder facilitates an online community for users to evolve and share images.
  • Users can branch from and continue evolving images created by others.
  • The neuroevolution of augmenting topologies (NEAT) algorithm enables increasing image complexity.

Main Results:

  • Picbreeder demonstrates a unique proliferation of evolved images through collaborative branching.
  • The system leverages collective user intelligence for artifact evolution.
  • The approach shows promise for generating diverse and complex artifacts in subjective domains.

Conclusions:

  • Collaborative interactive evolution (CIE) in Picbreeder shows significant potential for artifact generation.
  • The system's architecture and user interaction model drive image proliferation.
  • Lessons learned from Picbreeder can inform the development of future CIE systems.