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The evolution of emergent computation.

J P Crutchfield1, M Mitchell

  • 1Physics Department, University of California, Berkeley, CA 94720, USA.

Proceedings of the National Academy of Sciences of the United States of America
|November 7, 1995
PubMed
Summary

Evolutionary processes can develop advanced information processing in decentralized systems. Researchers analyzed particle-based logic in pattern-forming systems to understand emergent computation for natural and engineered systems.

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Area of Science:

  • Computational biology
  • Artificial intelligence
  • Complex systems

Background:

  • Decentralized spatially extended systems can exhibit complex emergent behaviors.
  • Understanding the mechanisms of emergent computation is crucial for both natural and artificial systems.

Purpose of the Study:

  • To explicate the mechanisms of emergent computation in decentralized systems.
  • To investigate how evolutionary processes can lead to sophisticated information processing.

Main Methods:

  • Analysis of particle-based logic within pattern-forming systems.
  • Employing evolutionary algorithms to discover computational methods.

Main Results:

  • A simple evolutionary process successfully discovered sophisticated emergent information processing methods.
  • The study elucidated the underlying mechanisms of this emergent computation.

Conclusions:

  • Evolutionary processes are capable of generating complex computational capabilities in decentralized systems.
  • Findings are relevant for understanding natural information processing and for designing novel parallel computing architectures.

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