6 papers
Explainable Information Design
Yiling Chen, Tao Lin, Wei Tang +1
Optimal signaling schemes in information design (Bayesian persuasion) often involve randomization or disconnected partitions of state space, which might be too intricate to be audi…
Learning a Game by Paying the Agents
Brian Hu Zhang, Tao Lin, Yiling Chen +1
We study the problem of learning the utility functions of no-regret learning agents in a repeated normal-form game. Differing from most prior literature, we introduce a principal w…
Generalized Principal-Agent Problem with a Learning Agent
Tao Lin, Yiling Chen
In classic principal-agent problems such as Stackelberg games, contract design, and Bayesian persuasion, the agent best responds to the principal's committed strategy. We study rep…
WOMAC: A Mechanism For Prediction Competitions
Siddarth Srinivasan, Tao Lin, Connacher Murphy +3
Competitions are widely used to identify top performers in judgmental forecasting and machine learning, and the standard competition design ranks competitors based on their cumulat…
User-Creator Feature Polarization in Recommender Systems with Dual Influence
Tao Lin, Kun Jin, Andrew Estornell +3
Recommender systems serve the dual purpose of presenting relevant content to users and helping content creators reach their target audience. The dual nature of these systems natura…
Bias Detection Via Signaling
Yiling Chen, Tao Lin, Ariel D. Procaccia +2
We introduce and study the problem of detecting whether an agent is updating their prior beliefs given new evidence in an optimal way that is Bayesian, or whether they are biased t…