Convergence Analysis and Strategy Control of Evolutionary Games with Imitation Rule on Toroidal Grid: A Full Version
Ge Chen, Yongyuan Yu

TL;DR
This paper provides the first rigorous convergence analysis of evolutionary games with imitation rules on two-dimensional toroidal grids, offering insights into strategy control and the influence of fixed nodes on the system's equilibrium.
Contribution
It proves convergence for multiple evolutionary games on grids and introduces strategy control methods, including the Minimum Agent Consensus Control problem.
Findings
Proves convergence of evolutionary prisoner's dilemma, snowdrift, and stag hunt games on grids.
Shows fixed defection node can lead all nodes to defection.
Demonstrates at least four fixed cooperation nodes are needed to ensure cooperation.
Abstract
This paper investigates discrete-time evolutionary games with a general stochastic imitation rule on the toroidal grid, which is a grid network with periodic boundary conditions. The imitation rule has been considered as a fundamental rule to the field of evolutionary game theory, while the grid is treated as the most basic network and has been widely used in the research of spatial (or networked) evolutionary games. However, currently the investigation of evolutionary games on grids mainly uses simulations or approximation methods, while few strict analysis is carried out on one-dimensional grids. This paper proves the convergence of evolutionary prisoner's dilemma, evolutionary snowdrift game, and evolutionary stag hunt game with the imitation rule on the two-dimensional grid, for the first time to our best knowledge. Simulations show that our results may almost reach the critical…
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Taxonomy
TopicsEvolutionary Game Theory and Cooperation · Evolution and Genetic Dynamics · Mathematical and Theoretical Epidemiology and Ecology Models
