  In the classical Bayesian persuasion model an informed player and an
uninformed one engage in a static interaction. The informed player, the sender,
knows the state of nature, while the uninformed one, the receiver, does not.
The informed player partially shares his private information with the receiver
and the latter then, based on her belief about the state, takes an action. This
action determines, together with the state of nature, the utility of both
players. We consider a dynamic Bayesian persuasion situation where the state of
nature evolves according to a Markovian law. In this repeated persuasion model
an optimal disclosure strategy of the sender should, at any period, balance
between getting high stage payoff and future implications on the receivers'
beliefs. We discuss optimal strategies under different discount factors and
characterize when the asymptotic value achieves the maximal value possible.
