• DocumentCode
    1797239
  • Title

    From ADP to the brain: Foundations, roadmap, challenges and research priorities

  • Author

    Werbos, Paul J.

  • Author_Institution
    Eng. Directorate, Nat. Sci. Found., Arlington, VA, USA
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    107
  • Lastpage
    111
  • Abstract
    This paper defines and discusses "Mouse Level Computational Intelligence" (MCLI) as a grand challenge for the coming century. It provides a specific roadmap to reach that target, citing relevant work and review papers and discussing the relation to funding priorities in two NSF funding activities. The ongoing Energy, Power and Adaptive Systems program (EPAS) and the recent initiative in Cognitive Optimization and Prediction (COPN). It elaborates on the first step, "vector intelligence," a challenge in the development of universal learning systems, which itself will require considerable new research to attain. This in turn is a crucial prerequisite to true functional understanding of how mammal brains achieve such general learning capabilities.
  • Keywords
    learning (artificial intelligence); COPN; EPAS program; MCLI; cognitive optimization and prediction; energy power and adaptive systems program; learning capabilities; mouse level computational intelligence; universal learning systems; vector intelligence; Approximation methods; Biological neural networks; Forecasting; Learning systems; Mice; Optimization; Vectors; ADP; Bayesian; control component; optimization; prediction; robust; stochastic processes; universal learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889359
  • Filename
    6889359