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Related Experiment Videos

Coevolving predator and prey robots: do "arms races" arise in artificial evolution?

S Nolfi1, D Floreano

  • 1Institute of Psychology, National Research Council, Viale Marx 15, Rome, Italy. stefano@kant.irmkant.rm.cnr.it

Artificial Life
|June 3, 1999
PubMed
Summary

Coevolution in artificial evolution can drive complexity and enhance adaptation. In evolutionary robotics, simple, adaptable strategies may outperform complex ones against evolving competitors.

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Area of Science:

  • Evolutionary computation
  • Artificial intelligence
  • Robotics

Background:

  • Coevolution, the reciprocal evolution of competing populations, can enhance adaptation.
  • Evolutionary "arms races" may drive increasing complexity in competing systems.

Purpose of the Study:

  • Investigate coevolution's role in evolutionary robotics.
  • Determine conditions leading to evolutionary "arms races."
  • Compare adaptive power of coevolution versus simple evolution.

Main Methods:

  • Analysis of coevolutionary dynamics in artificial evolution.
  • Simulations within the context of evolutionary robotics.
  • Comparative study of coevolved versus simply evolved populations.

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Main Results:

  • Coevolution can lead to evolutionary "arms races" in robotics.
  • Artificial coevolution demonstrates higher adaptive power than simple evolution in certain scenarios.
  • Analysis of coevolved populations reveals adaptive advantages of simple, modifiable strategies.

Conclusions:

  • Coevolution offers enhanced adaptive capabilities in artificial evolution.
  • Simple, adaptable strategies can be more effective than complex, general ones in coevolutionary robotics.
  • Understanding coevolutionary dynamics is key to optimizing artificial evolution strategies.