Spatial mean-field games for combatting corruption propagation

This paper provides a comprehensive mean-field model of corruption and its spatio-temporal and network connection effects. It is shown that optimizing the long-term honest people through state distribution (mean-field) will help to combat corruption propagation. Consequently, we bridge the gap between existing theories of different fields of research in order to draw a conclusive picture of corruption on the micro-, meso- and macroscopic level. The networking aspect of the model brings an interesting feature to the corruption propagation depending on the degree of the nodes and indirectly their number of multi-hop connections. The paper also investigates the effects of control strategies from both centralized and decentralized perspective to combat corruption.