Computational ability of cells based on cell dynamics and adaptability

Toshiyuki Nakagaki, Atsushi Tero, Ryo Kobayashi, Isamu Onishi, Tomoyuki Miyaji

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Learning how biological systems solve problems could help to design new methods of computation. Information processing in simple cellular organisms is interesting, as they have survived for almost 1 billion years using a simple system of information processing. Here we discuss a well-studied model system: the large amoeboid Physarum plasmodium. This amoeba can find approximate solutions for combinatorial optimization problems, such as solving a maze or a shortest network problem. In this report, we describe problem solving by the amoeba, and the computational methods that can be extracted from biological behaviors. The algorithm designed based on Physarum is both simple and useful.

Original languageEnglish
Pages (from-to)57-81
Number of pages25
JournalNew Generation Computing
Volume27
Issue number1
DOIs
Publication statusPublished - Nov 1 2008

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Adaptability
Information Processing
Cell
Combinatorial optimization
Biological systems
Computational methods
Learning Systems
Combinatorial Optimization Problem
Biological Systems
Computational Methods
Approximate Solution
Model

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Computational ability of cells based on cell dynamics and adaptability. / Nakagaki, Toshiyuki; Tero, Atsushi; Kobayashi, Ryo; Onishi, Isamu; Miyaji, Tomoyuki.

In: New Generation Computing, Vol. 27, No. 1, 01.11.2008, p. 57-81.

Research output: Contribution to journalArticle

Nakagaki, Toshiyuki ; Tero, Atsushi ; Kobayashi, Ryo ; Onishi, Isamu ; Miyaji, Tomoyuki. / Computational ability of cells based on cell dynamics and adaptability. In: New Generation Computing. 2008 ; Vol. 27, No. 1. pp. 57-81.
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