  We consider a team game reward, and we derive a stochastic Pontryagin's
maximum principle for distributed stochastic differential systems with
decentralized noisy information structures. Our methodology utilizes the semi
martingale representation theorem, variational methods, and backward stochastic
differential equations. Furthermore, we derive necessary and sufficient
optimality conditions that characterize team and person-by-person optimality of
decentralized strategies.
  Finally, we apply the stochastic maximum principle to several examples from
the application areas of communications, filtering and control.
