Optimal Control of an Unknown Linear Process with Learning

Optimal control of a linear process with unknown parameters is considered when the horizon is infinite and rewards are discounted. Active learning strategies are considered, i.e., agents consider the information value of possible actions, as well as current reward. Distributional assumptions are minimal in that no restriction to conjugate families is made. Convergence of beliefs and actions is established.