Predicting Agent Strategy Mix in Heterogeneous Populations

Prior research has identified agent behaviors or strategies that can develop and sustain mutually beneficial cooperative relationships with like-minded agents and can resist exploitation from selfish agents. Evolutionary tournaments with different strategies can model scenarios where agents periodically adopt strategies that are outperforming others in the population. However, such experiments can be computationally costly and hence it can be difficult to prescribe a strategy choice for a rational agent given environmental conditions like task distribution, strategy mix in the population, etc. A preferred approach, and the one pursued in this paper, is to analytically capture the dynamics of the strategy mix in the population under an evolutionary tournament. Such an analytical model can be used to predict the long-range winning strategy, which is the strategy to be preferred given the environmental conditions and the initial strategy distribution.