  In this paper, we investigate a decentralized stochastic control problem with
two agents, where a part of the memory of the second agent is also available to
the first agent at each instance of time. We derive a structural form for
optimal control strategies which allows us to restrict their domain to a set
which does not grow in size with time. We also present a dynamic programming
(DP) decomposition which can utilize our results to derive optimal strategies
for arbitrarily long time horizons. Since obtaining optimal control strategies
by solving this DP decomposition is computationally intensive, we present
potential resolutions in the form of simplified strategies by imposing
additional conditions on our model, and an approximation technique which can be
used to implement our results with a bounded loss of optimality.
