• DocumentCode
    3241663
  • Title

    Perception and prediction — A connectionist model

  • Author

    Iyer, Laxmi R. ; Seng-Beng Ho

  • Author_Institution
    Temasek Labs., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2013
  • fDate
    16-19 April 2013
  • Firstpage
    25
  • Lastpage
    32
  • Abstract
    Generating appropriate responses to incoming stimuli is a fundamental task of an organism. However, in order to generate intelligent responses, it is important to have a deeper understanding of the environment, and make predictions based on this knowledge. Although the ability to make predictions is intrinsic in humans and many animals, it is still a difficult task for a machine with no in built knowledge about the situation. In this paper we present a biologically inspired neural network model that predicts the future trajectory of a moving object after observing its current trajectory.
  • Keywords
    neural nets; biologically inspired neural network; connectionist model; moving object trajectory; perception; prediction; Animals; Biological system modeling; Brain modeling; Hippocampus; Predictive models; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Human-like Intelligence (CIHLI), 2013 IEEE Symposium on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/CIHLI.2013.6613261
  • Filename
    6613261