Dynamic principal agent model based on CMDP

Dynamic principal agent models are formulated based on constrained Markov decision process (CMDP), in which conditions are given that the state space of the system is countable and the agent chooses his actions from a countable action set. If the principal has finite alternative contracts to select, it is shown that the optimal contract solution and the corresponding optimal policy can be obtained by linear programming under the discounted criterion and average criterion. The paper is supported by Zhejiang Provincial Nature Science Foundation of China (701017) and by Scientific Research Fund of Zhejiang Provincial Education Department.