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Maze-solving by an amoeboid organism

Author

Listed:
  • Toshiyuki Nakagaki

    (Bio-Mimetic Control Research Center, RIKEN, Shimoshidami
    Local Spatio-Temporal Functions Laboratory, RIKEN)

  • Hiroyasu Yamada

    (Bio-Mimetic Control Research Center, RIKEN, Shimoshidami
    Local Spatio-Temporal Functions Laboratory, RIKEN
    Research Institute for Electronic Science, Hokkaido University)

  • Ágota Tóth

    (Department of Physical Chemistry University of Szeged)

Abstract

The plasmodium of the slime mould Physarum polycephalum is a large amoeba-like cell consisting of a dendritic network of tube-like structures (pseudopodia). It changes its shape as it crawls over a plain agar gel and, if food is placed at two different points, it will put out pseudopodia that connect the two food sources. Here we show that this simple organism has the ability to find the minimum-length solution between two points in a labyrinth.

Suggested Citation

  • Toshiyuki Nakagaki & Hiroyasu Yamada & Ágota Tóth, 2000. "Maze-solving by an amoeboid organism," Nature, Nature, vol. 407(6803), pages 470-470, September.
    • Handle: RePEc:nat:nature:v:407:y:2000:i:6803:d:10.1038_35035159
    DOI: 10.1038/35035159
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    Citations

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    Cited by:

    1. Takatomo Mihana & Yuta Terashima & Makoto Naruse & Song-Ju Kim & Atsushi Uchida, 2018. "Memory Effect on Adaptive Decision Making with a Chaotic Semiconductor Laser," Complexity, Hindawi, vol. 2018, pages 1-8, April.
    2. Tero, Atsushi & Kobayashi, Ryo & Nakagaki, Toshiyuki, 2006. "Physarum solver: A biologically inspired method of road-network navigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 115-119.
    3. Andrew Adamatzky & Olivier Allard & Jeff Jones & Rachel Armstrong, 2017. "Evaluation of French motorway network in relation to slime mould transport networks," Environment and Planning B, , vol. 44(2), pages 364-383, March.
    4. Stamatios C Nicolis & Natalia Zabzina & Tanya Latty & David J T Sumpter, 2011. "Collective Irrationality and Positive Feedback," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-6, April.
    5. Shin Watanabe & Atsuko Takamatsu, 2014. "Transportation Network with Fluctuating Input/Output Designed by the Bio-Inspired Physarum Algorithm," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    6. Guangzhi Han & Haifeng Jiang & Liansheng Lu & Shanshan Ma & Shuo Xiao, 2018. "Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
    7. Xiaoge Zhang & Andrew Adamatzky & Felix T. S. Chan & Sankaran Mahadevan & Yong Deng, 2017. "Physarum solver: a bio-inspired method for sustainable supply chain network design problem," Annals of Operations Research, Springer, vol. 254(1), pages 533-552, July.
    8. Julian M L Budd & Krisztina Kovács & Alex S Ferecskó & Péter Buzás & Ulf T Eysel & Zoltán F Kisvárday, 2010. "Neocortical Axon Arbors Trade-off Material and Conduction Delay Conservation," PLOS Computational Biology, Public Library of Science, vol. 6(3), pages 1-25, March.
    9. Gao, Cai & Yan, Chao & Zhang, Zili & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "An amoeboid algorithm for solving linear transportation problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 179-186.
    10. Ohnishi, Teruaki & Okada, Osami & Shirakata, Hirofumi, 2013. "Morphological similarity of road networks and cracks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4127-4133.

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