• DocumentCode
    2447583
  • Title

    Pleasure propagation to reward predictors

  • Author

    Goh, Chern Kuan ; Nareyek, Alexander

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2010
  • fDate
    18-21 Aug. 2010
  • Firstpage
    62
  • Lastpage
    68
  • Abstract
    Learning has always been one of the core mechanics in computer games. Players learn specific battle mechanics, control schemes, and much more, which enables them to progress further through the game and experience pleasure. Previous studies on learning often focused on the learning of predictors (cues) for reward and their motivational properties, but fail to address the impact on pleasure. For example, the cue of a smell of chocolate will already produce a pleasure feeling, which means that apart from the motivational learning of the smell cue, something affected pleasure generation as well. In this paper, we perform an experimental study to investigate this relation of learning and pleasure. The study, in which 38 test subjects participated, used smile reactions to rewards of showing funny pictures as a primary measure of pleasure. The findings of the study demonstrate that experiment repetition leads to an increase in pleasure at the cue, a decrease in pleasure at the reward, and a potential relation between motivation and pleasure change at the cue.
  • Keywords
    behavioural sciences computing; computer games; entertainment; learning (artificial intelligence); computer game; learning; motivation; pleasure propagation; reward predictor; Atmospheric measurements; Copper; Electromyography; Games; Mice; Particle measurements; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games (CIG), 2010 IEEE Symposium on
  • Conference_Location
    Dublin
  • Print_ISBN
    978-1-4244-6295-7
  • Electronic_ISBN
    978-1-4244-6296-4
  • Type

    conf

  • DOI
    10.1109/ITW.2010.5593372
  • Filename
    5593372