Effects of strategy-migration direction and noise in the evolutionary spatial prisoner's dilemma

TL;DR

This paper investigates how strategy-migration direction and noise influence cooperation in spatial prisoner's dilemma games on various lattices, revealing that certain dynamics and noise levels optimize cooperation.

Contribution

It introduces a comparative analysis of voter-model-like and invasion-like strategy updates, highlighting the impact of noise and local structures on cooperation evolution.

Findings

Voter-model-like dynamics better support cooperation than invasion-like dynamics.

Maximum cooperation occurs at medium or zero noise levels.

Local interaction structures critically influence cooperation outcomes.

Abstract

Spatial games are crucial for understanding patterns of cooperation in nature (and to some extent society). They are known to be more sensitive to local symmetries than e.g. spin models. This paper concerns the evolution of the prisoner's dilemma game on regular lattices with three different types of neighborhoods -- the von Neumann-, Moore-, and kagome types. We investigate two kinds of dynamics for the players to update their strategies (that can be unconditional cooperator or defector). Depending on the payoff difference, an individual can adopt the strategy of a random neighbor (a voter-model-like dynamics, VMLD), or impose its strategy on a random neighbor, i.e., invasion-like dynamics (IPLD). In particular, we focus on the effects of noise, in combination with the strategy dynamics, on the evolution of cooperation. We find that VMLD, compared to IPLD, better supports the spreading and sustaining of cooperation. We see that noise has nontrivial effects on the evolution of cooperation: maximum cooperation density can be realized either at a medium noise level, in the limit of zero noise, or in both these regions. The temptation to defect and the local interaction structure determine the outcome. Especially, in the low noise limit, the local interaction plays a crucial role in determining the fate of cooperators. We elucidate these both by numerical simulations and mean-field cluster approximation methods.