• DocumentCode
    2785949
  • Title

    Adaptive connection to the world through self-organizing sensors and effectors

  • Author

    Cariani, Peter

  • Author_Institution
    Massachusetts Eye & Ear Infirmary, Boston, MA, USA
  • fYear
    1990
  • fDate
    5-7 Sep 1990
  • Firstpage
    73
  • Abstract
    The realm of devices composed of adaptive sensing, computing, and effecting elements is surveyed, and contemporary devices are categorized accordingly. A new class of adaptive devices, those which adaptively construct their sensors and effectors, is presented. Such complement those which perform adaptive computations and could be used for adaptively constructing appropriate feature and action primitives for connectionist devices, thereby determining the real-world semantic categories within which the computational optimizations take place. Networks of such semantically adaptive elements would be capable of open-ended generation of new, orthogonal signal types, not logically reducible to preexisting types. An alternative conception of neurons as adaptive temporal elements utilizing the dynamic properties of excitable membranes is briefly outlined
  • Keywords
    adaptive systems; neural nets; neurophysiology; self-adjusting systems; action primitives; adaptive computations; adaptive devices; adaptive sensing; adaptive temporal elements; computational optimizations; connectionist devices; excitable membranes; orthogonal signal types; real-world semantic categories; self-organizing sensors; semantically adaptive elements; Biomembranes; Ear; Laboratories; Machine learning; Neural networks; Neurons; Organisms; Predictive models; Sensor phenomena and characterization; Signal generators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
  • Conference_Location
    Philadelphia, PA
  • ISSN
    2158-9860
  • Print_ISBN
    0-8186-2108-7
  • Type

    conf

  • DOI
    10.1109/ISIC.1990.128442
  • Filename
    128442