Amoeba-based emergent computing: Combinatorial optimization and autonomous meta-problem solving

Masashi Aono, Masahiko Hara, Kazuyuki Aihara, Toshinori Munakata

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Here we demonstrate a computing system employing an amoeba of a true slime mold Physarum known as a model organism for studying cellular information processing. The system works as a neurocomputer that exhibits high optimization capability in solving various problems including the traveling salesman problem.Additionally, we present a new technique that we call "autonomous meta-problem solving." In this approach, our system not only can solve a given problem but also can find new problems and then determine solutions by exploiting the amoeba's unique searching ability and spontaneous behavior.

Original languageEnglish
Pages (from-to)89-108
Number of pages20
JournalInternational Journal of Unconventional Computing
Volume6
Issue number2
Publication statusPublished - 2010 May 26
Externally publishedYes

Keywords

  • Actomyosin
  • Chaos
  • Fluctuations
  • Meta-problem solving
  • Molecular computing
  • Neural network
  • Optimization
  • Physarum
  • Self-organization
  • Spontaneous destabilization

ASJC Scopus subject areas

  • Computer Science(all)

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