USING EVOLUTIONARY GAMES THEORY FOR PLAYERS BEHAVIOR ANALYSIS IN COMPETITIVE SHOOTING GAMES: A LITERATURE REVIEW

Автор(и)

  • Luka Baryshych
  • Igor Baklan

DOI:

https://doi.org/10.34185/1991-7848.itmm.2021.01.012

Ключові слова:

game theory, cybersports, evolutionary games, behavior analysis, replicator strategy

Анотація

The paper is dedicated to the overview of current state of the evolutionary games approach to the building of environments to analyze players behavior. The evolutionary game theory applications differ from the orthodox game theory. Initially, it was used to address problems in evolutionary biology and later was suited for broader range of problems.
We will oversee the development of the evolutionary games theory in finance and its applications in behavior analysis in competitive gaming.
The paper is focused on replicator dynamics, learning model based on it and its possible application to behavior analysis based on fuzzy algorithms and approaches used in economics to be applied to the new emerging field of cybersports.

Посилання

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Roca, C. P., Cuesta, J. A., Sanchez, A. (2009). Evolutionary game theory: Temporal ´ and spatial effects beyond replicator dynamics. Physics of Life Reviews, 6(4), 208–249. doi:10.1016/j.plrev.2009.08.001

Borgers, T., Sarin, R. (1997). Learning Through Reinforcement and Replicator Dynamics. ¨ Journal of Economic Theory, 77(1), 1–14. doi:10.1006/jeth.1997.2319

Ippolito, P. (2019, September 20). Game Theory in Artificial Intelligence. Retrieved November 29, 2020, from https://towardsdatascience.com/game-theory-in-artificial-intelligence57a7937e1b88

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Опубліковано

2021-04-10

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