Population dynamics in evolutionary games on networks

Advances in control technology and communication technology have enabled the evolution of multi-agent networks into large-scale systems that could complete cooperative tasks which are more complicated than ever before. However, the requirements of efficiency, robustness and adaptability for multi-agent networks, when they are coordinated to execute these tasks, have increased dramatically in industrial and social fields in recent years. In this context, traditional control methodologies present some serious limitations. For example, many unexpected factors like information loss, time delays and perturbations can easily cause decision-making failure for strategic interactions in multi-agent systems, especially in some complex and hash environments.