• DocumentCode
    2655891
  • Title

    The Selection Dynamic Model Considering Anticipation in Social Population Learning

  • Author

    De-hai, LIU ; Wei-guo, WANG

  • Author_Institution
    Dongbei Univ. of Finance & Econ., Dalian
  • fYear
    2007
  • fDate
    20-22 Aug. 2007
  • Firstpage
    2449
  • Lastpage
    2454
  • Abstract
    The existing selection dynamic models in evolutionary game theory are still localized in the myopia hypothesis. This paper analyzes the social population have some anticipated ability, so they will consider the current payoff, the learning barriers and the payoff increasing rate, that´s the anticipative future payoff, when changing the current strategy. The paper describes the selected dynamic model considering anticipation based on the Sethi (1998), and proves that this model doesn´t accord with the weak payoff-positive dynamic. The population behavior hypothesis that they have some anticipated ability is fit for the social economy evolutionary phenomenon. At last, the paper analyzes a case that´s the Chinese rural labor transfer problem, where the existing research shows that the rural labor transfer behavior accords with the imitating behavior hypothesis, and uses the selection dynamic model considering anticipation to forecast the Chinese rural labor transferring trend until the 2050 year.
  • Keywords
    game theory; social sciences; Chinese rural labor transfer problem; evolutionary game theory; learning barriers; myopia hypothesis; rural labor transfer behavior; social economy evolutionary phenomenon; social population learning; Conference management; Economic forecasting; Engineering management; Finance; Financial management; Game theory; Learning systems; Mathematical model; Mathematics; Technology management; anticipation; evolutionary game theory; rural labor transfer; selection dynamic model; social population learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering, 2007. ICMSE 2007. International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-7-88358-080-5
  • Electronic_ISBN
    978-7-88358-080-5
  • Type

    conf

  • DOI
    10.1109/ICMSE.2007.4422205
  • Filename
    4422205