• DocumentCode
    1783074
  • Title

    Relative perception system and intelligence

  • Author

    Yujian Li

  • Author_Institution
    Coll. of Comput. Sci., Beijing Univ. of Technol., Beijing, China
  • fYear
    2014
  • fDate
    28-29 Sept. 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Physical symbol systems, for general intelligent action, take a physical stimulus as one object in the human world, whereas biological intelligent systems may take it as fundamentally different objects. For eliminating this conflict, the relative perception system hypothesis is proposed as a novel position for the nature of intelligence, based on the principle of world´s relativity. From the hypothesis, different relative perception systems, artificial or natural, may have very different understandings of the world, because they observe a relative world of physical objects for producing intelligent behavior. Intelligent behavior is a sequence of actions and operations that it can appropriately choose to achieve a task. Intelligence is an ability of a relative perception system to produce such sequences that may be computational or non-computational, and can be measured by the relative perception intelligence quotient, which is the weighted sum of scores in performing a selected set of tasks. Relative AI is advocated as a new paradigm for artificial intelligence, claiming that different kinds of relative perception systems may have very different understandings of the world, and no brain models can implement the human mind without human body.
  • Keywords
    artificial intelligence; artificial intelligence; intelligence; intelligent behavior; relative AI; relative perception intelligence quotient; relative perception system hypothesis; worlds relativity principle; Artificial intelligence; Biological system modeling; Birds; Brain modeling; Computers; Robots; Relative perception system; intelligence; physical symbol system; principle of world´s relativity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multisensor Fusion and Information Integration for Intelligent Systems (MFI), 2014 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6731-5
  • Type

    conf

  • DOI
    10.1109/MFI.2014.6997674
  • Filename
    6997674