There has been an increase in attention toward systems involving large
numbers of small players, giving rise to the theory of mean field games,
mean field type control and nonlinear Markov games. Exhibiting various
real world problems involving major and minor agents, this book presents
a systematic continuous-space approximation approach for mean-field
interacting agents models and mean-field games models. After
describing Markov-chain methodology and a modeling of mean-field
interacting systems, the text presents various structural conditions on
the chain to yield respective socio-economic models, focusing on
migration models via binary interactions. The specific applications are
wide-ranging - including inspection and corruption, cyber-security,
counterterrorism, coalition building and network growth, minority games,
and investment policies and optimal allocation - making this book
relevant to a wide audience of applied mathematicians interested in
operations research, computer science, national security, economics, and
finance.