• DocumentCode
    1880507
  • Title

    Bacterial communities: a microbiological model for swarm intelligence

  • Author

    Flikkema, Paul G. ; Leid, Jeffrey G.

  • Author_Institution
    Dept. of Electr. Eng., Northern Arizona Univ., Flagstaff, AZ, USA
  • fYear
    2005
  • fDate
    8-10 June 2005
  • Firstpage
    416
  • Lastpage
    419
  • Abstract
    Bacteria are highly efficient agents that sense, compute, and actuate. Moreover, they can form robust interspecies networks - bacterial communities - via sophisticated communication protocols. We assert that the improved understanding of these communities in the last decade provides a new model for swarm intelligence with distinct advantages, including ease of laboratory experimentation, explicit coupling of communication and behavior, and intergenerational dynamics. The first part of this paper provides a brief overview of bacterial communities in the context of swarm intelligence. The second part describes a promising new application of SI principles inspired by bacterial communities: the design of robust networked embedded and real-time systems.
  • Keywords
    artificial intelligence; biology; microorganisms; bacterial community; embedded system; intergenerational dynamics; microbiological model; real-time system; swarm intelligence; Biological system modeling; Biology computing; Chemicals; Communication system control; Embedded computing; Microorganisms; Particle swarm optimization; Protocols; Real time systems; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE
  • Print_ISBN
    0-7803-8916-6
  • Type

    conf

  • DOI
    10.1109/SIS.2005.1501655
  • Filename
    1501655