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Application of Nash Equilibrium in Two-Person Games

Published: 09 January 2022 Publication History

Abstract

Game theory is the study of the ways in which interacting choices of economic agents produce outcomes with respect to the preferences of those agents. The outcomes in question might have been intended by none of the agents. Here we want to start with solving Nash Equilibria of general two person problems and then specify to the discussion of the game of chicken, which is symmetric and the payoff matrix for both players satisfy certain constraints we will mention later. Finally, we attempted to find the optimal strategy for the first player, considering Nash Equilibria and a game with objective of winning over the opponent. And we believe future studies in this field may take advantage of techniques like reinforcement learning.]

References

[1]
The Stanford Encyclopedia of Philosophy (2019), Game Theory, Game Theory (Stanford Encyclopedia of Philosophy)
[2]
Robert J. Vanderbei (2014), Linear Programming: Foundations and Extensions, Springer Science+Business Media, New York
[3]
Joel N. Franklin (1980), Methods of Mathematical Economics, Springer-Verlag, New York
[4]
John F. Nash (1950), Equilibrium Points in n-Person Games, National Academy of Sciences, Vol. 36, No. 1 (Jan. 15, 1950), pp. 48-49
[5]
Rowland, Todd and Weisstein, Eric W. "Antisymmetric Matrix." From MathWorld–A Wolfram Web Resource. https://mathworld.wolfram.com/AntisymmetricMatrix.html
[6]
Howard E. Haber (2015), Notes on antisymmetric matrices and the pfaffian, pfaffian2.dvi (ucsc.edu)
[7]
Ochs Jack (1995), Games with Unique, Mixed Strategy Equilibria: An Experimental Study, Games and Economic Behavior, Vol 10, No. 1, July 1995, pp. 202-217
[8]
Jun Tanimoto, Hiroki Sagara (2007), Relationship between dilemma occurrence and the existence of a weakly dominant strategy in a two-player symmetric game, Biosystems, Vol 90, No. 1, July-August 2007, pp. 105-114
[9]
Xiaofeng Wang and Tuomas Sandholm (2002), Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games, Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games (nips.cc)
[10]
Drew Fudenberg and David M. Kreps (1992), Learning Mixed Equilibria, Learning mixed equilibria (mit.edu)

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ICIBE '21: Proceedings of the 7th International Conference on Industrial and Business Engineering
September 2021
411 pages
ISBN:9781450390644
DOI:10.1145/3494583
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 January 2022

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Author Tags

  1. Game Theory
  2. Game of Chicken
  3. Nash Equilibrium

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