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We study fair allocation of indivisible public goods subject to cardinality (budget) constraints. In this model, we have n agents and m available public goods, and we want to select $k \leq m$ goods in a fair and efficient manner. We first…

Computer Science and Game Theory · Computer Science 2021-07-22 Jugal Garg , Pooja Kulkarni , Aniket Murhekar

Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals. The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the…

Econometrics · Economics 2021-07-14 Sukjin Han

A principal must allocate a set of heterogeneous tasks (or objects) among multiple agents. The principal has preferences over the allocation. Each agent has preferences over which tasks they are assigned, which are their private…

Theoretical Economics · Economics 2026-01-29 Quitzé Valenzuela-Stookey

Many policy problems involve designing individualized treatment allocation rules to maximize the equilibrium social welfare of interacting agents. Focusing on large-scale simultaneous decision games with strategic complementarities, we…

Econometrics · Economics 2024-11-12 Guanyi Wang

We study a dynamic model of Bayesian persuasion in sequential decision-making settings. An informed principal observes an external parameter of the world and advises an uninformed agent about actions to take over time. The agent takes…

Computer Science and Game Theory · Computer Science 2022-05-25 Jiarui Gan , Rupak Majumdar , Goran Radanovic , Adish Singla

A principal who values an object allocates it to one or more agents. Agents learn private information (signals) from an information designer about the allocation payoff to the principal. Monetary transfer is not available but the principal…

Theoretical Economics · Economics 2022-10-31 Yi-Chun Chen , Gaoji Hu , Xiangqian Yang

The maximum Nash social welfare (NSW) -- which maximizes the geometric mean of agents' utilities -- is a fundamental solution concept with remarkable fairness and efficiency guarantees. The computational aspects of NSW have been extensively…

Computer Science and Game Theory · Computer Science 2023-12-15 Pallavi Jain , Rohit Vaish

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has…

Computer Science and Game Theory · Computer Science 2017-12-06 Mattia Mazzoli , Angel Sanchez

Motivated by applications such as cloud platforms allocating GPUs to users or governments deploying mobile health units across competing regions, we study the dynamic allocation of a reusable resource to strategic agents with private…

Computer Science and Game Theory · Computer Science 2025-07-15 Yan Dai , Negin Golrezaei , Patrick Jaillet

One of the major concerns of targeting interventions on individuals in social welfare programs is discrimination: individualized treatments may induce disparities across sensitive attributes such as age, gender, or race. This paper…

Econometrics · Economics 2022-07-01 Davide Viviano , Jelena Bradic

Fraud can pose a challenge in many resource allocation domains, including social service delivery and credit provision. For example, agents may misreport private information in order to gain benefits or access to credit. To mitigate this, a…

Computer Science and Game Theory · Computer Science 2026-04-29 Sanmay Das , Fang-Yi Yu , Yuang Zhang

Sequential allocation is a simple allocation mechanism in which agents are given pre-specified turns and each agents gets the most preferred item that is still available. It has long been known that sequential allocation is not…

Computer Science and Game Theory · Computer Science 2016-02-23 Haris Aziz , Sylvain Bouveret , Jerome Lang , Simon Mackenzie

Ensuring AI models align with human values is essential for their safety and functionality. Reinforcement learning from human feedback (RLHF) leverages human preferences to achieve this alignment. However, when preferences are sourced from…

Machine Learning · Computer Science 2025-02-10 Ryan Bahlous-Boldi , Li Ding , Lee Spector , Scott Niekum

We consider transferable-utility profit-sharing games that arise from settings in which agents need to jointly choose one of several alternatives, and may use transfers to redistribute the welfare generated by the chosen alternative. One…

Theoretical Economics · Economics 2019-09-26 Moshe Babaioff , Uriel Feige

The First Fundamental Theorem of Welfare Economics assumes that welfare-bearing agents are autonomous and implicitly relies on a binary distinction between autonomy and instrumentality. Welfare subjects are those who have autonomy and…

Theoretical Economics · Economics 2026-04-24 Elija Perrier

We initiate the study of multidimensional Bayesian utility maximization, focusing on the unit-demand setting where values are i.i.d. across both items and buyers. The seminal result of Hartline and Roughgarden '08 studies simple,…

Computer Science and Game Theory · Computer Science 2025-02-18 Kira Goldner , Taylor Lundy

We study hidden-action principal-agent problems in which a principal commits to an outcome-dependent payment scheme (called contract) so as to incentivize the agent to take a costly, unobservable action leading to favorable outcomes. In…

Computer Science and Game Theory · Computer Science 2022-08-18 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

We study a dynamic allocation problem in which $T$ sequentially arriving divisible resources are to be allocated to a number of agents with linear utilities. The marginal utilities of each resource to the agents are drawn stochastically…

Optimization and Control · Mathematics 2023-06-27 Santiago R. Balseiro , Shangzhou Xia

We study the power of item-pricing as a tool for approximately optimizing social welfare in a combinatorial market. We consider markets with $m$ indivisible items and $n$ buyers. The goal is to set prices to the items so that, when agents…

Computer Science and Game Theory · Computer Science 2015-11-10 Michal Feldman , Nick Gravin , Brendan Lucier

Existing AI alignment approaches assume that preferences are static, which is unrealistic: our preferences change, and may even be influenced by our interactions with AI systems themselves. To clarify the consequences of incorrectly…

Artificial Intelligence · Computer Science 2024-05-29 Micah Carroll , Davis Foote , Anand Siththaranjan , Stuart Russell , Anca Dragan