  This paper concerns the recursive utility maximization problem under partial
information. We first transform our problem under partial information into the
one under full information. When the generator of the recursive utility is
concave, we adopt the variational formulation of the recursive utility which
leads to a stochastic game problem and a characterization of the saddle point
of the game is obtained. Then, we study the K-ignorance case and explicit
saddle points of several examples are obtained. At last, when the generator of
the recursive utility is smooth, we employ the terminal perturbation method to
characterize the optimal terminal wealth.
