• DocumentCode
    2186102
  • Title

    Evolutionary Approach to Negotiation in Game AI

  • Author

    Iuhasz, Gabriel ; Munteanu, Victor Ion ; Negru, Viorel

  • Author_Institution
    Dept. of Comput. Sci., West Univ. of Timisoara, Timisoara, Romania
  • fYear
    2013
  • fDate
    23-26 Sept. 2013
  • Firstpage
    296
  • Lastpage
    302
  • Abstract
    As modern games become more and more sophisticated graphically, so does the level of artificial intelligence that animates them thus, the larger the game budget, the more work is put into improving the AI. Unfortunately many of these games feature AIs that are standalone and do not communicate with each other, they do not try to negotiate in order to improve their individual standing. The current work focuses on analysing existing game types in order to establish types of negotiation that can be achieved between AI entities. Moreover, an evolutionary approach which focuses on achieving negotiation between these entities and tackles the problem of having multiple negotiation items with discrete values is presented.
  • Keywords
    artificial intelligence; computer games; evolutionary computation; AI game; artificial intelligence; evolutionary approach; multiple negotiation items; Artificial intelligence; Contracts; Games; Genetic algorithms; Hidden Markov models; Sociology; Statistics; Artificial Intelligence; Evolutionary Algorithm; Games; Negotiation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2013 15th International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-1-4799-3035-7
  • Type

    conf

  • DOI
    10.1109/SYNASC.2013.46
  • Filename
    6821163