PhD Thesis Proposal - Curtis Bechtel

Title: Incentivizing Efficient Delegation without Payments
 
Date and Time: Thursday, Feb 20, 2025 at 12:00pm
 
Location: Ginsburg Hall (GCS) 502C
 
Committee: Shaddin Dughmi (Chair), David Kempe, Shanghua Teng, Vatsal Sharan, Ruolin Li (external)
 
Abstract: In delegation problems, a principal wants to search through a stochastic space of feasible solutions for one maximizing their utility, but they lack the ability to conduct this search on their own. Instead, they must delegate this search problem to one or more untrusted agents with distinct utility functions. The principal is then faced with the problem of designing a mechanism that incentivizes agents to find and propose a solution maximizing their utility. Importantly, the principal's power is limited to announcing which feasible solutions they would accept or reject, so we don't allow the principal to offer direct transfers of value, either positive or negative, for any outcome. Despite this limitation, there often exist mechanisms under which the principal is guaranteed a constant-factor approximation of their first-best utility. In this work, we propose three broad approaches to modeling delegation problems that address different aspects of the problem: combinatorial search and solution constraints, additive costs for searching, and delegating to multiple agents. We then show how the principal can achieve competitive approximations for several variants of each of these approaches.

Location: Ginsburg Hall (GCS) - 502C

Audiences: Everyone Is Invited

Contact: Curtis Bechtel