Information content of coevolutionary game landscapes

TL;DR

This paper analyzes the information content of coevolutionary game landscapes, examining how network structures and payoff matrices influence the complexity and features of these landscapes.

Contribution

It introduces a method to analyze game landscapes through their information content, focusing on the effects of payoff rescaling and population structure.

Findings

Network structure impacts landscape complexity.

Rescaled payoffs alter landscape features.

Structured populations differ from well-mixed ones.

Abstract

Coevolutionary game dynamics is the result of players that may change their strategies and their network of interaction. For such games, and based on interpreting strategies as configurations, strategy-to-payoff maps can be defined for every interaction network, which opens up to derive game landscapes. This paper presents an analysis of these game landscapes by their information content. By this analysis, we particularly study the effect of a rescaled payoff matrix generalizing social dilemmas and differences between well-mixed and structured populations.