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We explore the deliberate infusion of ambiguity into the design of contracts. We show that when the agent is ambiguity-averse and hence chooses an action that maximizes their minimum utility, the principal can strictly gain from using an…

Computer Science and Game Theory · Computer Science 2024-09-17 Paul Dütting , Michal Feldman , Daniel Peretz , Larry Samuelson

Following the recent literature on make take fees policies, we consider an exchange wishing to set a suitable contract with several market makers in order to improve trading quality on its platform. To do so, we use a principal-agent…

Trading and Market Microstructure · Quantitative Finance 2021-03-09 Bastien Baldacci , Dylan Possamaï , Mathieu Rosenbaum

We revisit the well-studied problem of budget-feasible procurement, where a buyer with a strict budget constraint seeks to acquire services from a group of strategic providers (the sellers). During the last decade, several strategyproof…

Computer Science and Game Theory · Computer Science 2021-07-22 Eric Balkanski , Pranav Garimidi , Vasilis Gkatzelis , Daniel Schoepflin , Xizhi Tan

We analyze a principal-agent procurement problem in which the principal (she) is unaware some of the marginal cost types of the agent (he). Communication arises naturally as some types of the agent may have an incentive to raise the…

Theoretical Economics · Economics 2025-10-27 Alejandro Francetich , Burkhard C. Schipper

In many first-price auctions, bidders face considerable strategic uncertainty: They cannot perfectly anticipate the other bidders' bidding behavior. We propose a model in which bidders do not know the entire distribution of opponent bids…

Theoretical Economics · Economics 2022-03-30 Bernhard Kasberger

We study the incentivized information acquisition problem, where a principal hires an agent to gather information on her behalf. Such a problem is modeled as a Stackelberg game between the principal and the agent, where the principal…

Machine Learning · Computer Science 2023-08-08 Siyu Chen , Jibang Wu , Yifan Wu , Zhuoran Yang

A central problem in business concerns the optimal allocation of limited resources to a set of available tasks, where the payoff of these tasks is inherently uncertain. In credit card fraud detection, for instance, a bank can only assign a…

Machine Learning · Computer Science 2022-02-10 Toon Vanderschueren , Bart Baesens , Tim Verdonck , Wouter Verbeke

The prevalence and importance of algorithmic two-sided marketplaces has drawn attention to the issue of fairness in such settings. Algorithmic decisions are used in assigning students to schools, users to advertisers, and applicants to job…

Machine Learning · Computer Science 2023-06-19 Siddartha Devic , David Kempe , Vatsal Sharan , Aleksandra Korolova

We study a single task allocation problem where each worker connects to some other workers to form a network and the task requester only connects to some of the workers. The goal is to design an allocation mechanism such that each worker is…

Computer Science and Game Theory · Computer Science 2022-01-19 Xiuzhen Zhang , Yao Zhang , Dengji Zhao

We study a new class of contract design problems where a principal delegates the execution of multiple projects to a set of agents. The principal's expected reward from each project is a combinatorial function of the agents working on it.…

Computer Science and Game Theory · Computer Science 2025-06-09 Tal Alon , Matteo Castiglioni , Junjie Chen , Tomer Ezra , Yingkai Li , Inbal Talgam-Cohen

We suggest that the analysis of incomplete contracting developed by law and economics researchers can provide a useful framework for understanding the AI alignment problem and help to generate a systematic approach to finding solutions. We…

Artificial Intelligence · Computer Science 2018-04-13 Dylan Hadfield-Menell , Gillian Hadfield

Many-to-many matching with contracts is studied in the framework of revealed preferences. All preferences are described by choice functions that satisfy natural conditions. Under a no-externality assumption individual preferences can be…

Computer Science and Game Theory · Computer Science 2020-03-05 Daniel Lehmann

A principal and an agent face symmetric uncertainty about the value of two correlated projects for the agent. The principal chooses which project values to publicly discover and makes a proposal to the agent, who accepts if and only if the…

Theoretical Economics · Economics 2022-11-22 Eitan Sapiro-Gheiler

This paper tackles challenges in pricing and revenue projections due to consumer uncertainty. We propose a novel data-based approach for firms facing unknown consumer type distributions. Unlike existing methods, we assume firms only observe…

Theoretical Economics · Economics 2024-05-28 Duarte Gonçalves , Bruno A. Furtado

This work proposes a way to align statistical modeling with decision making. We provide a method that propagates the uncertainty in predictive modeling to the uncertainty in operational cost, where operational cost is the amount spent by…

Machine Learning · Statistics 2015-03-19 Theja Tulabandhula , Cynthia Rudin

Algorithmic contract design studies scenarios where a principal incentivizes an agent to exert effort on her behalf. In this work, we focus on settings where the agent's type is drawn from an unknown distribution, and formalize an offline…

Computer Science and Game Theory · Computer Science 2025-01-27 Paul Duetting , Michal Feldman , Tomasz Ponitka , Ermis Soumalias

We consider the problem of budget feasible mechanism design proposed by Singer (2010), but in a Bayesian setting. A principal has a public value for hiring a subset of the agents and a budget, while the agents have private costs for being…

Computer Science and Game Theory · Computer Science 2015-10-22 Eric Balkanski , Jason D. Hartline

We study principal-agent problems in which a principal commits to an outcome-dependent payment scheme (a.k.a. contract) so as to induce an agent to take a costly, unobservable action. We relax the assumption that the principal perfectly…

Computer Science and Game Theory · Computer Science 2021-06-02 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Experts advising decision-makers are likely to display expertise which varies as a function of the problem instance. In practice, this may lead to sub-optimal or discriminatory decisions against minority cases. In this work we model such…

Artificial Intelligence · Computer Science 2023-10-27 Axel Abels , Tom Lenaerts , Vito Trianni , Ann Nowé

Motivating careerists is challenging for political organizations. Without explicit contracts, careerists often pander to public opinions or their superiors' preferences. Worse, when tasked with implementing these distorted decisions, they…

General Economics · Economics 2026-05-15 Liqun Liu