Evolutionary Game Dynamics with Environmental Feedback in a Network with Two Communities.

Katherine Betz, Feng Fu, Naoki Masuda
Author Information
  1. Katherine Betz: Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, 14260-2900, USA.
  2. Feng Fu: Department of Mathematics, Dartmouth College, Hanover, NH, 03755, USA.
  3. Naoki Masuda: Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, 14260-2900, USA. naokimas@gmail.com. ORCID

Abstract

Recent developments of eco-evolutionary models have shown that evolving feedbacks between behavioral strategies and the environment of game interactions, leading to changes in the underlying payoff matrix, can impact the underlying population dynamics in various manners. We propose and analyze an eco-evolutionary game dynamics model on a network with two communities such that players interact with other players in the same community and those in the opposite community at different rates. In our model, we consider two-person matrix games with pairwise interactions occurring on individual edges and assume that the environmental state depends on edges rather than on nodes or being globally shared in the population. We analytically determine the equilibria and their stability under a symmetric population structure assumption, and we also numerically study the replicator dynamics of the general model. The model shows rich dynamical behavior, such as multiple transcritical bifurcations, multistability, and anti-synchronous oscillations. Our work offers insights into understanding how the presence of community structure impacts the eco-evolutionary dynamics within and between niches.

Keywords

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Grants

  1. JPMJMS2021/Moonshot Research and Development Program
  2. 2052720/National Science Foundation
  3. 2204936/National Science Foundation
  4. JP21H04595/Japan Society for the Promotion of Science London
  5. JP23H03414/Japan Society for the Promotion of Science London

MeSH Term

Game Theory
Biological Evolution
Mathematical Concepts
Population Dynamics
Humans
Models, Biological
Ecosystem
Computer Simulation
Feedback
Animals
Environment

Word Cloud

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