A vital introduction to the stochastic analysis tools which play an increasing role in the probabilistic approach to optimization problems, including stochastic control and stochastic differential games. As one of the few books on game theory and the theory of stochastic differential games, this book will be helpful to graduate students and young researchers interested in stochastic differential equations and the probabilistic approach to stochastic control, as well as mean field games and the control of McKean–Vlasov dynamics. The theory is illustrated by application to several areas, including application to models of systemic risk, macroeconomic growth, flocking/schooling, crowd behavior, and predatory trading. Based on the author's lecture notes, this is the first title in the SIAM Series on Financial Mathematics.