• DocumentCode
    1716138
  • Title

    Algorithmic and evolutionary game theory and their applications in Internet of Things

  • Author

    Dae-Ki Kang

  • Author_Institution
    Dongseo Univ., Busan, South Korea
  • fYear
    2013
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Algorithmic game theory concerns algorithms and their analyses of finding equilibria in multi-agent strategic environments. Nash has shown that, in his seminal work, there is always an equilibrium where all agents can stay with their best responses. Evolutionary game theory concerns on stability and dynamics of agent population through differential reproduction governed by mutation and natural selection. Recently we have seen huge potentials of applying research achievements of algorithmic and evolutionary game theories to the domain of Internet of Things, which constitutes an intelligent network of humans, things and services.
  • Keywords
    Internet of Things; evolutionary computation; game theory; multi-agent systems; Internet of Things; Nash equilibrium; agent population dynamics; agent population stability; algorithmic game theory; differential reproduction; evolutionary game theory; intelligent network; multiagent strategic environment; mutation; natural selection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Technology (ICACT), 2013 15th International Conference on
  • Conference_Location
    PyeongChang
  • ISSN
    1738-9445
  • Print_ISBN
    978-1-4673-3148-7
  • Type

    conf

  • Filename
    6488125