  We formulate a two-team linear quadratic stochas- tic dynamic game featuring
two opposing teams each with decentralized information structures. We introduce
the concept of mutual quadratic invariance (MQI), which, analogously to
quadratic invariance in (single team) decentralized control, defines a class of
interacting information structures for the two teams under which optimal linear
feedback control strate- gies are easy to compute. We show that, for zero-sum
two- team dynamic games, structured state feedback Nash (saddle- point)
equilibrium strategies can be computed from equivalent structured disturbance
feedforward saddle point equilibrium strategies. However, for nonzero-sum games
we show via a counterexample that a similar equivalence fails to hold. The
results are illustrated with a simple yet rich numerical example that
illustrates the importance of the information structure for dynamic games.
