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This paper provides a general framework to explore the possibility of agenda manipulation-proof and proper consensus-based preference aggregation rules, so powerfully called in doubt by a disputable if widely shared understanding of Arrow's…

Theoretical Economics · Economics 2022-10-10 Stefano Vannucci

Multilateral index numbers are often used to make claims about welfare, such as treating PPPs as cross-country costs of living or real incomes as indicators of living standards. However, such interpretations may not be consistent with the…

General Economics · Economics 2025-12-11 Hubert Wu

We consider the problem of Adverse Selection and optimal derivative design within a Principal-Agent framework. The principal's income is exposed to non-hedgeable risk factors arising, for instance, from weather or climate phenomena. She…

Computational Engineering, Finance, and Science · Computer Science 2007-10-31 U. Horst , S. Moreno

The implementation of a supervision and incentive process for identical workers may lead to wage variance that stems from employer and employee optimization. The harder it is to assess the nature of the labor output, the more important such…

Econometrics · Economics 2018-06-06 Nitsa Kasir , Idit Sohlberg

In the Ultimatum Game (UG) one player, named "proposer", has to decide how to allocate a certain amount of money between herself and a "responder". If the offer is greater than or equal to the responder's minimum acceptable offer (MAO),…

Physics and Society · Physics 2018-04-04 Valerio Capraro

In classification with a reject option, the classifier is allowed in uncertain cases to abstain from prediction. The classical cost-based model of a reject option classifier requires the cost of rejection to be defined explicitly. An…

Machine Learning · Computer Science 2021-02-01 V. Franc , D. Prusa , V. Voracek

We study fair division of indivisible goods in a single-parameter environment. In particular, we develop truthful social welfare maximizing mechanisms for fairly allocating indivisible goods. Our fairness guarantees are in terms of solution…

Computer Science and Game Theory · Computer Science 2019-01-29 Siddharth Barman , Ganesh Ghalme , Shweta Jain , Pooja Kulkarni , Shivika Narang

Current alignment pipelines presume a single, universal notion of desirable behavior. However, human preferences often diverge across users, contexts, and cultures. As a result, disagreement collapses into the majority signal and minority…

Machine Learning · Computer Science 2025-06-10 Daniel Halpern , Evi Micha , Ariel D. Procaccia , Itai Shapira

Shapley values are widely used for model-agnostic data valuation and feature attribution, yet they implicitly assume contributors are interchangeable. This can be problematic when contributors are dependent (e.g., reused/augmented data or…

Machine Learning · Computer Science 2026-02-11 Kiljae Lee , Ziqi Liu , Weijing Tang , Yuan Zhang

Consider an unobservable $M|G|1$ queue with preemptive-resume scheduling and two priority classes. Customers are strategic and may join the premium class for a fee. We analyze the resulting equilibrium outcomes, equilibrium stability, and…

Computer Science and Game Theory · Computer Science 2020-03-03 Jonathan Chamberlain , David Starobinski

This study considers a model of the income distribution of agents whose pairwise interaction is asymmetric and price-invariant. Asymmetric transactions are typical for chain-trading groups who arrange their business such that commodities…

Probability · Mathematics 2009-11-11 Alexander M. Chebotarev

We consider the problem of fair allocation of $m$ indivisible items to a group of $n$ agents with subsidy (money). Our work mainly focuses on the allocation of chores but most of our results extend to the allocation of goods as well. We…

Computer Science and Game Theory · Computer Science 2023-07-11 Xiaowei Wu , Cong Zhang , Shengwei Zhou

We consider the fundamental mechanism design problem of approximate social welfare maximization under general cardinal preferences on a finite number of alternatives and without money. The well-known range voting scheme can be thought of as…

Computer Science and Game Theory · Computer Science 2014-09-12 Aris Filos-Ratsikas , Peter Bro Miltersen

Motivated by applications such as college admission and insurance rate determination, we propose an evaluation problem where the inputs are controlled by strategic individuals who can modify their features at a cost. A learner can only…

Computer Science and Game Theory · Computer Science 2020-11-05 Nika Haghtalab , Nicole Immorlica , Brendan Lucier , Jack Z. Wang

Reinforcement learning from human feedback usually models preferences using a reward function that does not distinguish between people. We argue that this is unlikely to be a good design choice in contexts with high potential for…

Inspired by recent works on evolutionary graph theory, an area of growing interest in mathematical and computational biology, we present the first known examples of undirected structures acting as suppressors of selection for any fitness…

Populations and Evolution · Quantitative Biology 2017-11-01 Fernando Alcalde Cuesta , Pablo González Sequeiros , Álvaro Lozano Rojo

In selection processes such as hiring, promotion, and college admissions, implicit bias toward socially-salient attributes such as race, gender, or sexual orientation of candidates is known to produce persistent inequality and reduce…

Computers and Society · Computer Science 2022-06-08 Anay Mehrotra , Bary S. R. Pradelski , Nisheeth K. Vishnoi

In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requirement with the goal of minimizing expected ex post regret,…

Computer Science and Game Theory · Computer Science 2012-08-07 Paul Duetting , Felix Fischer , Pitchayut Jirapinyo , John K. Lai , Benjamin Lubin , David C. Parkes

How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of machine learning systems. Stringent parity constraints on…

Artificial Intelligence · Computer Science 2020-12-09 Angie Peng , Jeff Naecker , Ben Hutchinson , Andrew Smart , Nyalleng Moorosi

Existing observational approaches for learning human preferences, such as inverse reinforcement learning, usually make strong assumptions about the observability of the human's environment. However, in reality, people make many important…

Machine Learning · Statistics 2021-10-29 Cassidy Laidlaw , Stuart Russell
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