题　目：Dynamic Contract Design with Learning

嘉　宾：Shiyuan Wang, Ph.D. Candidate, Tsinghua University

主持人：花成 副教授 上海交通大学安泰经济与管理学院

时　间：2024年12月25日（周三）14:00-15:30

地　点：安泰楼A403室

内容简介：

We investigate a contract design problem with moral hazard, that is, the effort exerted by the agent is unobservable to the principal. Additionally, the agent’s capability is unknown to both the principal and the agent in the beginning and must be learned over time. Both principal and agent aim to maximize their respective expected utility through the entire contract horizon. The goal is to design a contract that maximize principal’s expected utility corresponding to agent’s best response. Due to the intractability of solving this problem directly, we adopt a regret minimization approach and aim to design contracts that achieve an optimal regret rate. We define a proper notion of regret for this problem and provide a novel regret lower bound. Subsequently, we develop two dynamic contracts that are easy-to-implement and achieve the optimal regret rate. In addition, we will briefly introduce our related works in decision theory with learning. This includes a follow-up work considering multiple types of capable agents. Even considering two types of capable agent, the straightforward extensions of our previous method prove ineffective. We will also discuss a dynamic information design problem with moral hazard.

演讲人简介：

Shiyuan Wang is a PhD candidate at the School of Economics and Management, Tsinghua University, expected to graduate in June 2025. She obtained a Bachelor's degree in Computer Science and Technology from Tsinghua University in 2020. Her research focuses on data-driven decision-making problems, including online optimization in revenue management, and dynamic contract design and information design with learning. Her papers, "Online Joint Assortment-Inventory Optimization under MNL Choices" and "Dynamic Contract Design with Learning," are currently under major revision for Operations Research. She spent the 2023-2024 academic year as a visiting scholar at the Fuqua School of Business and six months in 2019 at the Institute for Data, Systems, and Society at MIT. She also completed a six-month internship at JD.com in 2021.

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