Organizer(s):

Vasilis Gkatzelis, Drexel University

Shengwu Li, Harvard University

Daniel Schoepflin, DIMACS

Description

A common obstacle in the design of effective mechanisms in the presence of strategic self-interested agents is the need for preference elicitation. This often arises when the participating agents hold some of the information regarding their private preferences that the designer needs in order to reach a desired outcome. The designer could simply ask the agents to volunteer this information, but there are many reasons why this may be against their best interest, motivating them either to deny this request or to strategically volunteer false information. The most obvious obstacle is that the mechanism needs to be “incentive compatible”, i.e., to appropriately reward or penalize the agent so that their optimal strategy is to report the true information.

However, incentive compatibility may not be enough: even if a mechanism is incentive compatible, the agents may still hesitate to participate or to report truthfully, unless the mechanism also possesses other appealing properties such as i) simplicity, which would allow the agents to easily identify their optimal strategy, ii) transparency, so that the agents need not trust the designer in order to participate, and iii) privacy, so that the agents need not worry about the ways in which their data is going to be used and the privacy cost that they will incur as a result.

In this workshop we will focus on all these aspects of preference elicitation, bringing together an interdisciplinary set of speakers and attendees from economics, computer science, and operations research. We will discuss ways to formalize simplicity, privacy, and transparency, and examine their implications using both theory and data. One particular focus is the design of dynamic mechanisms with better incentive properties than their static equivalents.

Confirmed speakers:

• Jason Hartline, Northwestern University
• Andrew Mackenzie, Rutgers University
• Lea Nagel, Stanford University
• Roberto Saitto, Stanford University
• Daniel Schoepflin, DIMACS
• Shiri Ron, Weizmann Institute of Science
• Clay Thomas, Microsoft
• Peter Troyan, Harvard University
• Carmine Ventre, King's College London

Call For Participation

Presentations at this workshop are by invitation but others are welcome to attend. There is no fee to attend but registration is required. Please register using the button at the bottom of the page. Space is limited, so please register early if you plan to attend.

Poster session: The workshop will feature a poster session. If you would like to present a poster please apply using the form referenced below. The deadline for submitting a poster is September 15, 2024. [Now closed]

Request support: There are limited funds available to support travel by those whose attendance is contingent on support. The deadline for requesting support is September 4, 2024. If you need support, please do not book your tickets until you hear from us!

To apply for travel support or to apply to submit a poster: Please complete this form. (It is a single form through which you can apply for support or to present a poster, or both.) We especially encourage diverse and inclusive participation. We will prioritize applications for support from students presenting posters and those from minority or underrepresented groups.

Presented in association with the SF on Mechanisms & Algorithms to Augment Human Decision Making.