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The evolution of parallel cellular machines: toward evolware

M Sipper1

  • 1Logic Systems Laboratory, Swiss Federal Institute of Technology, Lausanne, Switzerland. Moshe.Sipper@di.epfl.ch

Bio Systems
|January 1, 1997
PubMed
Summary
This summary is machine-generated.

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Researchers evolved parallel cellular machines using a cellular programming approach to solve computational problems. This evolvable hardware (evolware) demonstrates the potential for creating adaptable, self-improving systems.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Bio-inspired Systems

Background:

  • The concept of evolving machines is experiencing a resurgence, driving advancements in bio-inspired systems and evolvable hardware.
  • Cellular programming offers a novel methodology for creating adaptive computational systems.

Purpose of the Study:

  • To describe the cellular programming approach for evolving parallel cellular machines.
  • To demonstrate the application of this approach to diverse computational problems.

Main Methods:

  • Utilized a cellular programming methodology to evolve parallel cellular machines.
  • Applied the evolved machines to six distinct computational tasks: density, synchronization, ordering, boundary computation, thinning, and random number generation.

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Main Results:

  • Successfully evolved parallel cellular machines capable of solving the targeted computational problems.
  • Demonstrated the efficacy of the cellular programming approach in creating functional evolvable hardware.

Conclusions:

  • The cellular programming approach is a viable method for developing evolvable hardware (evolware).
  • This research opens possibilities for future applications in areas like bioware, highlighting ongoing work and future research directions.