Strategic Persuasion Through Information Timeliness
Information TheoryComputer Science and Game TheoryNetworking and Internet Architecture
Summary
The authors study a communication game where one side (the sender) decides when to send truthful updates about a changing state, while the other side (the receiver) tries to estimate that state. The sender wants the receiver to believe the state is 1 as much as possible, even if it isn't, by strategically timing updates. The receiver chooses whether to trust the sender’s updates or rely on prior knowledge, balancing accuracy and influence. The authors find optimal strategies for the sender to achieve this, including methods for handling multiple sources and receivers. Their work shows that just by controlling when updates happen, the sender can influence what the receiver believes.
Authors
Ahmet Bugra Gundogan, Melih Bastopcu
Abstract
We study a dynamic strategic communication problem in which a sender controls the timing of truthful updates from binary continuous-time Markov sources. The receiver chooses between a zero-order-hold estimator that follows the sender's updates and a prior-only default estimator, aiming to maximize a weighted correct-estimation utility. In contrast, the sender seeks to persuade the receiver to estimate the state as 1, regardless of the true state. This misalignment leads to a Stackelberg game in which the sender, as the leader, commits to state-dependent Poisson update rates, and the receiver, as the follower, decides whether to follow the sender's messages. The sender maximizes the long-term average time that the receiver's estimate equals 1, subject to a conditional intensity budget and a participation constraint (PC) ensuring that following the sender's messages does not degrade the receiver's average utility relative to its prior information. For a single source, we show that the sender's optimal policy allocates a minimum state-0 update intensity to the undesired state-0, just enough to satisfy the PC, and the remaining budget to the desired state-1. For multiple sources with heterogeneous minimum state-0 update intensities, we develop a branch-and-bound algorithm that typically avoids exhaustive search. Finally, we extend the solution to multiple receivers over dedicated channels. Our results show that controlling timeliness alone enables the sender to persuade the receiver and increase its utility.