• DocumentCode
    565202
  • Title

    Design tools for artificial nervous systems

  • Author

    Scheffer, Louis K.

  • Author_Institution
    Howard Hughes Med. Inst., Howard, WI, USA
  • fYear
    2012
  • fDate
    3-7 June 2012
  • Firstpage
    717
  • Lastpage
    722
  • Abstract
    Electronic and biological systems both perform complex information processing, but they use very different techniques. Though electronics has the advantage in raw speed, biological systems have the edge in many other areas. They can be produced, and indeed self-reproduce, without expensive and finicky factories. They are tolerant of manufacturing defects, and learn and adapt for better performance. In many cases they can self-repair damage. These advantages suggest that biological systems might be useful in a wide variety of tasks involving information processing. So far, all attempts to use the nervous system of a living organism for information processing have involved selective breeding of existing organisms. This approach, largely independent of the details of internal operation, is used since we do not yet understand how neural systems work, nor exactly how they are constructed. However, as our knowledge increases, the day will come when we can envision useful nervous systems and design them based upon what we want them to do, as opposed to variations on what has been already built. We will then need tools, corresponding to our Electronic Design Automation tools, to help with the design. This paper is concerned with what such tools might look like.
  • Keywords
    artificial intelligence; bioinformatics; electronic design automation; neurophysiology; artificial nervous systems; biological systems; complex information processing; electronic design automation tools; electronic systems; internal operation details; living organism; manufacturing defects; neural systems; selective organisms breeding; self-repair damage; Animals; Chemicals; Logic gates; Neurons; Biological systems; Design Automation; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design Automation Conference (DAC), 2012 49th ACM/EDAC/IEEE
  • Conference_Location
    San Francisco, CA
  • ISSN
    0738-100X
  • Print_ISBN
    978-1-4503-1199-1
  • Type

    conf

  • Filename
    6241584