• DocumentCode
    586561
  • Title

    Intrinsic motivation mechanisms for competence acquisition

  • Author

    Santucci, Vieri G. ; Baldassarre, Gianluca ; Mirolli, Marco

  • Author_Institution
    Lab. of comput. embodied Neurosci. (LOCEN), Ist. di Sci. e Tecnol. della Cognizione (ISTC), Rome, Italy
  • fYear
    2012
  • fDate
    7-9 Nov. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In the computational literature intrinsic motivations have been connected to the possibility of developing more autonomous and versatile agents. Despite the growing theoretical understanding of the distinction between functions and mechanisms of intrinsic motivations, the implications of the distinction have not been exploited in specific models. In particular, knowledge-based mechanisms are widely used to implement intrinsic motivations signals for the acquisition of competences, leading to inappropriate learning signals. In this paper we analyse and compare, with the support of simple grid-world simulations, different mechanisms that can be used to implement competence acquisition through intrinsic motivations, describing their limits and strengths and highlighting which features are best suited for the acquisition of competence.
  • Keywords
    control engineering; learning (artificial intelligence); mobile robots; psychology; autonomous agent; competence acquisition; grid-world simulation; intrinsic motivation mechanism; intrinsic motivations signal; knowledge-based mechanism; learning signal; reinforcement learning; versatile agent; Analytical models; Computational modeling; Computer architecture; Education; Laboratories; Neuroscience; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Development and Learning and Epigenetic Robotics (ICDL), 2012 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4673-4964-2
  • Electronic_ISBN
    978-1-4673-4963-5
  • Type

    conf

  • DOI
    10.1109/DevLrn.2012.6400835
  • Filename
    6400835