Information content of coevolutionary game landscapes
This work provides theoretical insights into coevolutionary games, which is incremental for researchers in evolutionary game theory and network science.
The paper analyzed coevolutionary game landscapes by their information content to understand the effects of rescaled payoff matrices and differences between well-mixed and structured populations, finding insights into how these factors influence game dynamics.
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.