A multi-agent based migration model for evolving cooperation in the spatial N-player snowdrift game

Abstract

In recent years, there has been an increased interest in using agent-based simulation models to investigate the evolution of cooperative behaviour in spatial evolutionary games. However, the relationship between individual player mobility (or migration) and population dynamics is not clear. In this paper, we investigate the impacts of alternative migration mechanisms in the spatial N-player Snowdrift game. Here, agents occupy sites in a two-dimensional toroidal lattice. Specific game instances are created by nominating N sites from each of the local neighbourhoods. We use a genetic algorithm to evolve agent game-playing strategies. In addition, agents have an opportunity to migrate to different sites in the lattice at regular intervals. Key parameters in our model include the migration rate, the actual dispersal distance, the "take-over" scheme, the group size N, and the relative cost-to-benefit ratio of the game. Detailed simulation experiments show that the proposed model is able to promote cooperation in a population of mobile agents. However, the magnitude of the dispersal distance plays a significant role in determining population dynamics. Our findings help to further understand how migratory (mobility) patterns affect evolutionary processes