High-Accuracy Approximation of Evolutionary Pairwise Games on Complex Networks
arXiv:2301.05192 · doi:10.1016/j.chaos.2023.113602
Abstract
Previous studies have shown that the topological properties of a complex network, such as heterogeneity and average degree, affect the evolutionary game dynamics on it. However, traditional numerical simulations are usually time-consuming and demand a lot of computational resources. In this paper, we propose the method of dynamical approximate master equations (DAMEs) to accurately approximate the evolutionary outcomes on complex networks. We demonstrate that the accuracy of DAMEs supersedes previous standard pairwise approximation methods, and DAMEs require far fewer computational resources than traditional numerical simulations. We use prisoner's dilemma and snowdrift game on regular and scale-free networks to demonstrate the applicability of DAMEs. Overall, our method facilitates the investigation of evolutionary dynamics on a broad range of complex networks, and provides new insights into the puzzle of cooperation.
21 pages, 4 figures
References in corpus (10)
- Evolutionary games on graphs
- Evolutionary dynamics of group interactions on structured populations: A review
- Social diversity and promotion of cooperation in the spatial prisoner's dilemma game
- Effect of spatial structure on the evolution of cooperation
- Evolutionary Prisoner's Dilemma on heterogeneous Newman-Watts small-world network
- Social dilemmas in an online social network: the structure and evolution of cooperation
- Prisoner's Dilemma on community networks
- Cluster approximations for probabilistic systems: a new perspective of epidemiological modelling
- Zero temperature Glauber dynamics on complex networks
- Beyond pairwise strategy updating in the prisoner's dilemma game