ON STOCHASTIC INCENTIVE CONTROL PROBLEMS WITH PARTIAL DYNAMIC INFORMATION.

The authors consider a stochastic incentive decision problem with N less than 1 followers and decentralized static information, where the leader's dynamic information comprises only a linear combination of the follower's actions. An incentive policy, affine in this dynamic information, is obtained which yields the same overall performance as the policy the leader would obtain if he had observed the follower's actions separately. The existence conditions involved have been obtained explicitly for the case of finite probability spaces, and some challenging issues have been identified when the random variables are infinite-valued.