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Evolution and Collective Intelligence of the Electric Sheep

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Part of the Natural Computing Series book series (NCS)

Summary

Electric Sheep is a collective intelligence composed of 40,000 computers and people mediated by a genetic algorithm. It is made with an open source screen-saver that harnesses idle computers into a render farm with the purpose of animating and evolving artificial life-forms known as sheep. The votes of the users form the basis for a fitness function for exploring a space of abstract animations. Users also may design sheep by hand for inclusion in the gene pool.

The name Electric Sheep is an homage to Philip K. Dick’s novel Do Androids Dream of Electric Sheep; the basis for the film Blade Runner. The metaphor compares the screen-saver to the computer’s dream.

After the introduction, we dig into the system starting with Sect. 3.2 on its architecture and implementation. Sect. 3.3 covers the genetic code, including its basis in the equations of classic Iterated Function Systems. The equation is then generalized into the Fractal Flame algorithm, which translates the genetic code into an image. The next two sections treat color and motion.

Section 3.4 shows how the genetic algorithm decides which sheep die, which ones reproduce, and how. Section 3.5. defines the primary dataset and its limitations, and reports some of its statistics. Section 3.5.1 uses the dataset to determine that the genetic algorithm functions more as an amplifier of its human collaborators’ creativity rather than as a traditional genetic algorithm that optimizes a fitness function.

The goal of Electric Sheep is to create a self-supporting, network-resident life-form. Section 3.6. speculates on how to make the flock support more of a self-sustaining reaction rather than functioning as an amplifier. Finally, Sect. 3.6.1, explains how Dreams in High Fidelity addresses the support issue.

Keywords

  • Genetic Algorithm
  • Genetic Code
  • Peak Rating
  • Iterate Function System
  • Collective Intelligence

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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Draves, S. (2008). Evolution and Collective Intelligence of the Electric Sheep. In: Romero, J., Machado, P. (eds) The Art of Artificial Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72877-1_3

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  • DOI: https://doi.org/10.1007/978-3-540-72877-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72876-4

  • Online ISBN: 978-3-540-72877-1

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