• DocumentCode
    1436847
  • Title

    Biology: see it again-for the first time

  • Author

    Luke, Sean ; Hamahashi, Shugo ; Kyoda, Koji ; Ueda, Hiroki

  • Author_Institution
    Comput. Sci. Lab., Sony Corp., Tokyo, Japan
  • Volume
    13
  • Issue
    5
  • fYear
    1998
  • Firstpage
    6
  • Lastpage
    8
  • Abstract
    Computer science owes a huge debt to biological systems. The field came about largely as an attempt to understand and replicate the function and abilities of the brain. From this early lineage have sprung many subfields derived largely from biological metaphors: computer vision, neural networks, evolutionary computation, robotics, multiagent studies, and much of artificial intelligence. In some areas, the computer has bested its biological counterparts in efficiency and simplicity. But for many domains the biological “real thing” remains superior to the artificial algorithms that it inspired. While computer science has been simplifying its inspirations from biology, biologists have been catching up. Soon it will be possible to model entire neurosystems, gene-regulation mechanisms, evolutionary processes and even whole organisms on a computer. Given how much biological metaphors have inspired AI and computer science, biology can help reinvigorate many other AI subfields. Moreover, modeling and analysis promise to enable many things that have long been pipe dreams of autonomous robotics, artificial life, and cognitive science
  • Keywords
    artificial intelligence; biology computing; computer science; artificial intelligence; artificial life; biological metaphors; biological systems; biology; brain; cognitive science; computer science; computer vision; evolutionary computation; evolutionary processes; gene-regulation mechanisms; multiagent studies; neural networks; neurosystems; robotics; Artificial intelligence; Artificial neural networks; Biological neural networks; Biological system modeling; Biological systems; Biology computing; Computer science; Computer vision; Evolution (biology); Evolutionary computation;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems and their Applications, IEEE
  • Publisher
    ieee
  • ISSN
    1094-7167
  • Type

    jour

  • DOI
    10.1109/5254.722341
  • Filename
    722341