The discrete time discounted multi-objective Markov decision model with incomplete state observations is presented. The lexicographically order optimal problem is shown to be equivalent to the optimal problem of a one-reward Markov decision model with complete state observations. Copyright...

The discrete time discounted multi-objective Markov decision model with incomplete state observations is presented. The lexicographically order optimal problem is shown to be equivalent to the optimal problem of a one-reward Markov decision model with complete state observations. Copyright...

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...

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...

The goal of this paper is provide a theory of K-person non-stationary Markov games with unbounded rewards, for a countable state space and action spaces. We investigate both the finite and infinite horizon problems. We define the concept of strong Nash equilibrium and present conditions for both...