Structure coefficients and strategy selection in multiplayer games.

Alex McAvoy, Christoph Hauert
Author Information
  1. Alex McAvoy: Department of Mathematics, University of British Columbia, Vancouver, BC, Canada. alexmcavoy@gmail.com.
  2. Christoph Hauert: Department of Mathematics, University of British Columbia, Vancouver, BC, Canada.

Abstract

Evolutionary processes based on two-player games such as the Prisoner's Dilemma or Snowdrift Game are abundant in evolutionary game theory. These processes, including those based on games with more than two strategies, have been studied extensively under the assumption that selection is weak. However, games involving more than two players have not received the same level of attention. To address this issue, and to relate two-player games to multiplayer games, we introduce a notion of reducibility for multiplayer games that captures what it means to break down a multiplayer game into a sequence of interactions with fewer players. We discuss the role of reducibility in structured populations, and we give examples of games that are irreducible in any population structure. Since the known conditions for strategy selection, otherwise known as [Formula: see text]-rules, have been established only for two-player games with multiple strategies and for multiplayer games with two strategies, we extend these rules to multiplayer games with many strategies to account for irreducible games that cannot be reduced to those simpler types of games. In particular, we show that the number of structure coefficients required for a symmetric game with [Formula: see text]-player interactions and [Formula: see text] strategies grows in [Formula: see text] like [Formula: see text]. Our results also cover a type of ecologically asymmetric game based on payoff values that are derived not only from the strategies of the players, but also from their spatial positions within the population.

Keywords

References

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MeSH Term

Biological Evolution
Game Theory
Genetic Fitness
Humans
Linear Models
Markov Chains
Mathematical Concepts
Models, Biological
Population
Probability
Stochastic Processes

Word Cloud

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