We study a repeated information design problem faced by an informed sender who tries to
influence the behavior of a self-interested receiver. We consider settings where the receiver …

We study a dynamic model of Bayesian persuasion in sequential decision-making settings.
An informed principal observes an external parameter of the world and advises an …

Reinforcement learning (RL) is inspired by the way human infants and animals learn from
the environment. The setting is somewhat idealized because, in actual tasks, other agents in …

Network congestion games are a well-understood model of multi-agent strategic
interactions. Despite their ubiquitous applications, it is not clear whether it is possible to …

For common notions of correlated equilibrium in extensive-form games, computing an
optimal (eg, welfare-maximizing) equilibrium is NP-hard. Other equilibrium notions …

In Bayesian persuasion, an informed sender has to design a signaling scheme that
discloses the right amount of information so as to influence the behavior of a self-interested …

We study Bayesian automated mechanism design in unstructured dynamic environments,
where a principal repeatedly interacts with an agent, and takes actions based on the …

We introduce a unified framework for the study of multilevel mixed integer linear optimization
problems and multistage stochastic mixed integer linear optimization problems with …

We study an information-structure design problem (ie, a Bayesian persuasion problem) in an
online scenario. Inspired by the classic gambler's problem, consider a set of candidates who …

We study the problem of designing the optimal k-memory messaging scheme in a dynamic
environment. Specifically, a sender, who can perfectly observe the state of a dynamic …