Workshop on Mean Field Games on Networks

Mean Field Game (MFG) theory studies strategic decision problems in large populations of interacting agents, which is now widely applied in economics, financial markets, engineering, social science, and many other areas. The generalization of classical mean field game theory to the study of problems on networks that exhibit heterogeneity, bounded local connections, dynamic dependence, and uncertainties in structure is extremely important in terms of theoretical development and practical applications; it is the focus of the proposed workshop.

The objective of this workshop is to bring together researchers in applied mathematics, mean field games, network science, network games, and systems and control theory to exchange ideas and to work on the extensions of mean field game theory to dynamic game problems on heterogeneous large-scale networks. The expected outcome of the workshop is the significant development of the subject and consequently its enhanced progress in terms of mathematical theory, computational algorithms, and the applications methodologies of MFG on general networks. The workshop will offer a platform to present current results and stimulate discussions on the open challenges in this emerging field.