Persuading Farsighted Receivers in MDPs: the Power of Honesty

Bayesian persuasion studies the problem faced by an informed sender who strategically discloses information to influence the behavior of an uninformed receiver. Recently, a growing attention has been devoted to settings where the sender and the receiver interact sequentially, in which the receiver's decision-making problem is usually modeled as a Markov decision process (MDP). However, the literature focuses on computing optimal information-revelation policies (a.k.a.