• DocumentCode
    3661410
  • Title

    A comparative study between motivated learning and reinforcement learning

  • Author

    J. Graham;J. A. Starzyk;Z. Ni;H. He;T.-H. Teng;A.-H. Tan

  • Author_Institution
    School of EECS, Ohio Univ., Athens, USA
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper analyzes advanced reinforcement learning techniques and compares some of them to motivated learning. Motivated learning is briefly discussed indicating its relation to reinforcement learning. A black box scenario for comparative analysis of learning efficiency in autonomous agents is developed and described. This is used to analyze selected algorithms. Reported results demonstrate that in the selected category of problems, motivated learning outperformed all reinforcement learning algorithms we compared with.
  • Keywords
    "Robot kinematics","Planning"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2015 International Joint Conference on
  • Electronic_ISBN
    2161-4407
  • Type

    conf

  • DOI
    10.1109/IJCNN.2015.7280723
  • Filename
    7280723