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

Masashi Aono; Masahiko Hara; Kazuyuki Aihara; Toshinori Munakata

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

Masashi Aono, Masahiko Hara, Kazuyuki Aihara, Toshinori Munakata

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	89-108
Number of pages	20
Journal	International Journal of Unconventional Computing
Volume	6
Issue number	2
Publication status	Published - 2010
Externally published	Yes

Keywords

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

ASJC Scopus subject areas

Computer Science(all)

Cite this

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KW - Fluctuations

KW - Meta-problem solving

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KW - Spontaneous destabilization

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

Abstract

Keywords

ASJC Scopus subject areas

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