• DocumentCode
    2859342
  • Title

    An Application of Ant Colony Optimization to Decision Making on Affective Virtual Entities

  • Author

    Mocholi, Jose A. ; Jaen, Javier

  • Author_Institution
    Polytech. Univ. of Valencia, Valencia
  • fYear
    2007
  • fDate
    26-29 Sept. 2007
  • Firstpage
    419
  • Lastpage
    426
  • Abstract
    Learning is a never ending activity for humans; it takes place everywhere and even when we do not realize. However, current learning environments make students deal with lectures, mostly associated with low control of the situation and implicit motivation. In contrast, previous researches have shown that sports, games or hobbies are activities that make people reach optimal experiences where self-motivation, control of the situation, high level of concentration and enjoyment are present. Some current efforts to design next generation of learning environments make use of ubiquitous systems to encourage students to perform learning activities everywhere and at anytime. However, those approaches lack the affective factor related to optimal experiences. To address that problem we present eCoology, an edutainment application that creates a ubiquitous learning environment with emotional features, and discuss some experimental results obtained from users that tested eCoology.
  • Keywords
    augmented reality; computer aided instruction; computer games; decision making; entertainment; optimisation; ubiquitous computing; ant colony optimization; augmented reality game application; decision making; eCoology edutainment application; ubiquitous learning environment; virtual entity; Ant colony optimization; Automatic testing; Decision making; Feedback; Game theory; Humans; Information systems; Optimal control; Scientific computing; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Symbolic and Numeric Algorithms for Scientific Computing, 2007. SYNASC. International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-0-7695-3078-8
  • Type

    conf

  • DOI
    10.1109/SYNASC.2007.73
  • Filename
    4438132