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This is the second special issue of Dynamic Games and Applications on Mean Field Games (MFG, in short). The first was published in December 2013 and collected original papers on various aspects of the MFG theory and applications. The two issues aim at giving a wide overview of the emerging trends in this fast growing research area. An earlier snapshot of the research on MFG can be found in the special issue of Networks and Hetereogeneous Media [1]. The theory of MFG is a branch of Dynamic Games which aims at modeling and analyzing complex decision processes involving a large number of indistinguishable rational agents who have individually a very small influence on the overall system and are, on the other hand, influenced by the mass of the other agents. The name comes from particle physics where it is common to consider interactions among particles as an external mean field which influences the particles themselves. In spite of the optimization made by rational agents, playing the role of particles in such models, appropriate mean field equations can be derived to replace the many particles interactions by a single problem with an appropriately chosen external mean field which takes into account the global behavior of the individuals. The introduction of a social component in the optimization criteria makes this theory so flexible that it can be applied to various fields and, for this reason, it is attracting an increasing interest from economists (micro and macro), engineers, biologist describing the animal behavior, and possibly sociologists and urban planners.

Preface: DGAA 2nd Special Issue on Mean Field Games