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Related papers: Disappointment in Social Choice Protocols

200 papers

In many social-choice mechanisms the resulting choice is not the most preferred one for some of the participants, thus the need for methods to justify the choice made in a way that improves the acceptance and satisfaction of said…

Computer Science and Game Theory · Computer Science 2022-06-01 Sharadhi Alape Suryanarayana , David Sarne , Sarit Kraus

Any community in which membership is optional may eventually break apart, or fork. For example, forks may occur in political parties, business partnerships, social groups, cryptocurrencies, and federated governing bodies. Forking is…

Multiagent Systems · Computer Science 2023-12-11 Ben Abramowitz , Edith Elkind , Davide Grossi , Ehud Shapiro , Nimrod Talmon

In social choice theory with ordinal preferences, a voting method satisfies the axiom of positive involvement if adding to a preference profile a voter who ranks an alternative uniquely first cannot cause that alternative to go from winning…

Theoretical Economics · Economics 2025-04-01 Wesley H. Holliday

Elections involving a very large voter population often lead to outcomes that surprise many. This is particularly important for the elections in which results affect the economy of a sizable population. A better prediction of the true…

Computer Science and Game Theory · Computer Science 2018-01-31 Palash Dey , Pravesh K. Kothari , Swaprava Nath

Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholder preferences to create algorithmic systems that account for those stakeholders' values. Using algorithmic student assignment…

Computers and Society · Computer Science 2020-07-15 Samantha Robertson , Niloufar Salehi

We study deliberative social choice, where voters engage in small-group discussions to output collective preferences that are then aggregated by a social choice rule. We introduce a simple deliberation-via-matching protocol. In this…

Computer Science and Game Theory · Computer Science 2026-04-27 Kamesh Munagala , Qilin Ye , Ian Zhang

Social choice functions (SCFs) map the preferences of a group of agents over some set of alternatives to a non-empty subset of alternatives. The Gibbard-Satterthwaite theorem has shown that only extremely restrictive SCFs are strategyproof…

Computer Science and Game Theory · Computer Science 2022-03-30 Felix Brandt , Martin Bullinger , Patrick Lederer

This work contributes to a foundational question in economic theory: how do individual-level cognitive biases interact with collective choice mechanisms? We study a setting where voters hold intrinsic preference rankings over a set of…

Theoretical Economics · Economics 2026-02-24 Federico Fioravanti , Zoi Terzopoulou

A critical note on some of the existing proposals for performing the "delayed choice" experiment is placed. By abandoning the original idea and intention, some modern theoretical proposals and experimental evidence are simply incorrectly…

Quantum Physics · Physics 2012-11-08 M. Dugic

Preference cycles are prevalent in problems of decision-making, and are contradictory when preferences are assumed to be transitive. This contradiction underlies Condorcet's Paradox, a pioneering result of Social Choice Theory, wherein…

Algebraic Topology · Mathematics 2026-04-21 Ori Livson , Siddharth Pritam , Mikhail Prokopenko

We study the utilitarian distortion of social choice mechanisms under the recently proposed learning-augmented framework where some (possibly unreliable) predicted information about the preferences of the agents is given as input. In…

Computer Science and Game Theory · Computer Science 2025-02-11 Aris Filos-Ratsikas , Georgios Kalantzis , Alexandros A. Voudouris

Social choice has become a foundational component of modern machine learning systems. From auctions and resource allocation to the alignment of large generative models, machine learning pipelines increasingly aggregate heterogeneous…

Artificial Intelligence · Computer Science 2026-02-24 Zhiyu An , Wan Du

AI systems are often used to make or contribute to important decisions in a growing range of applications, including criminal justice, hiring, and medicine. Since these decisions impact human lives, it is important that the AI systems act…

Artificial Intelligence · Computer Science 2021-03-16 Duncan C McElfresh , Lok Chan , Kenzie Doyle , Walter Sinnott-Armstrong , Vincent Conitzer , Jana Schaich Borg , John P Dickerson

This paper studies a decentralized many-to-one matching market where preferences remain uncertain during the matching process. Institutions initiate matching by sending offers, and applicants decide whether to accept upon receiving them.…

Theoretical Economics · Economics 2025-11-14 Yu-Ting Ho

Facing an unknown situation, a person may not be able to firmly elicit his/her preferences over different alternatives, so he/she tends to express uncertain preferences. Given a community of different persons expressing their preferences…

Artificial Intelligence · Computer Science 2017-08-11 Yiru Zhang , Tassadit Bouadi , Arnaud Martin

We propose and axiomatize a new model of incomplete preferences under uncertainty, which we call \textit{hope-and-prepare preferences}. An act is considered more desirable than an other act when, and only when, both an optimistic…

Theoretical Economics · Economics 2025-07-29 Pierre Bardier , Bach Dong-Xuan , Van-Quy Nguyen

We consider a social choice problem where only a small number of people out of a large population are sufficiently available or motivated to vote. A common solution to increase participation is to allow voters use a proxy, that is, transfer…

Computer Science and Game Theory · Computer Science 2016-11-28 Gal Cohensius , Shie Manor , Reshef Meir , Eli Meirom , Ariel Orda

It is common to encounter the situation with uncertainty for decision makers (DMs) in dealing with a complex decision making problem. The existing evidence shows that people usually fear the extreme uncertainty named as the unknown. This…

Theoretical Economics · Economics 2021-08-05 Fang Liu

This paper presents some fundamental collective choice theory for information system designers, particularly those working in the field of computer-supported cooperative work. This paper is focused on a presentation of Arrow's Possibility…

Multiagent Systems · Computer Science 2007-05-23 Walter Eaves

Foundation models such as GPT-4 are fine-tuned to avoid unsafe or otherwise problematic behavior, such as helping to commit crimes or producing racist text. One approach to fine-tuning, called reinforcement learning from human feedback,…