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Dynamics of multi-player games

E Ben-Naim1, B Kahng1,2 and J S Kim1,2

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We analyse the dynamics of competitions with a large number of players. In our model, n players compete against each other and the winner is decided based on the standings: in each competition, the mth ranked player wins. We solve for the long time limit of the distribution of the number of wins for all n and m using scaling analysis of the nonlinear evolution equations, and find three different scenarios. When the best player wins, the standings are most competitive as there is one tier with a clear differentiation between strong and weak players. When an intermediate player wins, the standings are two-tier with equally strong players in the top tier and clearly-separated players in the lower tier. Interestingly, the size and the strength of the upper tier are nontrivial. When the worst player wins, the standings are least competitive as there is one tier in which all of the players are equal. We conclude that controlling the rank of the winner provides a way of controlling social inequalities.


Keywords

stochastic processes

nonlinear dynamics

interacting agent models

applications to game theory and mathematical economics

PACS

02.50.Le Decision theory and game theory

89.75.-k Complex systems

02.50.Ng Distribution theory and Monte Carlo studies

89.65.-s Social and economic systems

MSC

91A15 Stochastic games

91A46 Combinatorial games

91A25 Dynamic games

91A13 Games with infinitely many players

62P25 Applications to social sciences

Subjects

Computational physics

Statistical physics and nonlinear systems

Dates

Issue 07 (July 2006)

Received 28 April 2006, accepted for publication 15 June 2006

Published 11 July 2006



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