3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Estimating and Incentivizing Imperfect-Knowledge Agents with Hidden Rewards
Ilgin Dogan, Zuo-Jun Max Shen, Anil Aswani
In practice, incentive providers (i.e., principals) often cannot observe the reward realizations of incentivized agents, which is in contrast to many principal-agent models that ha…
cs.LG2023
Repeated Principal-Agent Games with Unobserved Agent Rewards and Perfect-Knowledge Agents
Ilgin Dogan, Zuo-Jun Max Shen, Anil Aswani
Motivated by a number of real-world applications from domains like healthcare and sustainable transportation, in this paper we study a scenario of repeated principal-agent games wi…
math.OC2021★ 3 cited
Regret Analysis of Learning-Based MPC with Partially-Unknown Cost Function
Ilgin Dogan, Zuo-Jun Max Shen, Anil Aswani
The exploration/exploitation trade-off is an inherent challenge in data-driven adaptive control. Though this trade-off has been studied for multi-armed bandits (MAB's) and reinforc…