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Using chemical reaction network theory to show stability of distributional dynamics in game theory
Author(s) -
Ross Cressman,
Vlastimil Křivan
Publication year - 2021
Publication title -
journal of dynamics and games
Language(s) - English
Resource type - Journals
eISSN - 2164-6074
pISSN - 2164-6066
DOI - 10.3934/jdg.2021030
Subject(s) - mathematical economics , game theory , replicator equation , uniqueness , stability (learning theory) , mathematics , population , extensive form game , prisoner's dilemma , group (periodic table) , distribution (mathematics) , repeated game , equilibrium selection , computer science , physics , mathematical analysis , demography , quantum mechanics , machine learning , sociology
This article shows how to apply results of chemical reaction network theory (CRNT) to prove uniqueness and stability of a positive equilibrium for pairs/groups distributional dynamics that arise in game theoretic models. Evolutionary game theory assumes that individuals accrue their fitness through interactions with other individuals. When there are two or more different strategies in the population, this theory assumes that pairs (groups) are formed instantaneously and randomly so that the corresponding pairs (groups) distribution is described by the Hardy–Weinberg (binomial) distribution. If interactions times are phenotype dependent the Hardy-Weinberg distribution does not apply. Even if it becomes impossible to calculate the pairs/groups distribution analytically we show that CRNT is a general tool that is very useful to prove not only existence of the equilibrium, but also its stability. In this article, we apply CRNT to pair formation model that arises in two player games (e.g., Hawk-Dove, Prisoner's Dilemma game), to group formation that arises, e.g., in Public Goods Game, and to distribution of a single population in patchy environments. We also show by generalizing the Battle of the Sexes game that the methodology does not always apply.

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