An Exact Dynamic Programming Solution for a Decentralized Two-Player Markov Decision Process

We present an exact dynamic programming solution for a finite-horizon decentralized two-player Markov decision process, where player 1 only has access to its own states, while player 2 has access to both player's states but cannot affect player 1's states. The solution is obtained by solving several centralized partially-observable Markov decision processes. We then conclude with several computational examples.