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Norms have been extensively proposed as coordination mechanisms for both agent and human societies. Nevertheless, choosing the norms to regulate a society is by no means straightforward. The reasons are twofold. First, the norms to choose…

Multiagent Systems · Computer Science 2017-04-04 Maite Lopez-Sanchez , Marc Serramia , Juan A. Rodriguez-Aguilar , Javier Morales , Michael Wooldridge

Social marketing is becoming increasingly important in contemporary business. Central to social marketing is quantifying how consumers choose between alternatives and how they influence each other. This work considers a new but simple…

Social and Information Networks · Computer Science 2014-05-05 Jeremy Chen

We consider the problem of social choice when transfers between agents are possible. This includes several canonical applications: public-good provision, management of a common resource, settlement of debts, and division of goods. The…

Theoretical Economics · Economics 2025-12-19 Gregorio Curello , Sam Jindani

Several rules for social choice are examined from a unifying point of view that looks at them as procedures for revising a system of degrees of belief in accordance with certain specified logical constraints. Belief is here a social…

Artificial Intelligence · Computer Science 2015-05-06 Rosa Camps , Xavier Mora , Laia Saumell

Social choice theory is the study of preference aggregation across a population, used both in mechanism design for human agents and in the democratic alignment of language models. In this study, we propose the representative social choice…

Machine Learning · Computer Science 2025-11-03 Tianyi Qiu

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

In economic theory, an agent chooses from available alternatives -- modeled as a set. In decisions in the field or in the lab, however, agents do not have access to the set of alternatives at once. Instead, alternatives are represented by…

Computer Science and Game Theory · Computer Science 2021-11-09 Paulo Oliva , Philipp Zahn

The task of learning to pick a single preferred example out a finite set of examples, an "optimal choice problem", is a supervised machine learning problem with complex, structured input. Problems of optimal choice emerge often in various…

Artificial Intelligence · Computer Science 2017-07-07 Marina Sapir

The way that people make choices or exhibit preferences can be strongly affected by the set of available alternatives, often called the choice set. Furthermore, there are usually heterogeneous preferences, either at an individual level…

Computer Science and Game Theory · Computer Science 2020-08-04 Kiran Tomlinson , Austin R. Benson

We propose a pseudo-market solution to resource allocation problems subject to constraints. Our treatment of constraints is general: including bihierarchical constraints due to considerations of diversity in school choice, or scheduling in…

Theoretical Economics · Economics 2020-11-09 Federico Echenique , Antonio Miralles , Jun Zhang

The school choice problem concerns the design and implementation of matching mechanisms that produce school assignments for students within a given public school district. In this note we define a simple student-optimal criterion that is…

Optimization and Control · Mathematics 2013-04-30 Sinan Aksoy , Adam Azzam , Chaya Coppersmith , Julie Glass , Gizem Karaali , Xueying Zhao , Xinjing Zhu

We study situations where a group of voters need to take a collective decision over a number of public issues, with the goal of getting a result that reflects the voters' opinions in a proportional manner. Our focus is on interconnected…

Computer Science and Game Theory · Computer Science 2025-09-25 Julian Chingoma , Umberto Grandi , Arianna Novaro

We discuss a novel microscopic model for collective decision-making interacting multi-agent systems. In particular we are interested in modeling a well known phenomena in the experimental literature called equality bias, where agents tend…

Physics and Society · Physics 2017-04-18 Pierluigi Vellucci , Mattia Zanella

To successfully navigate its environment, an agent must construct and maintain representations of the other agents that it encounters. Such representations are useful for many tasks, but they are not without cost. As a result, agents must…

Artificial Intelligence · Computer Science 2023-12-11 Max Taylor-Davies , Christopher G. Lucas

We consider an agent community wishing to decide on several binary issues by means of issue-by-issue majority voting. For each issue and each agent, one of the two options is better than the other. However, some of the agents may be…

Computer Science and Game Theory · Computer Science 2022-07-12 Shiri Alouf-Heffetz , Laurent Bulteau , Edith Elkind , Nimrod Talmon , Nicholas Teh

We consider a dynamic collective choice problem where a large number of players are cooperatively choosing between multiple destinations while being influenced by the behavior of the group. For example, in a robotic swarm exploring a new…

Systems and Control · Computer Science 2016-06-17 Rabih Salhab , Jerome Le Ny , Roland P. Malhamé

Social choice theory is a theoretical framework for analysis of combining individual preferences, interests, or welfare to reach a collective decision or social welfare in some sense. We introduce a new criterion for social choice protocols…

Multiagent Systems · Computer Science 2019-08-19 Mohammad Ali Javidian , Rasoul Ramezanian

This paper investigates the social optimum for a dynamic linear quadratic collective choice problem where a group of agents choose among multiple alternatives or destinations. The agents' common objective is to minimize the average cost of…

Optimization and Control · Mathematics 2025-06-12 Noureddine Toumi , Roland Malhamé , Jérôme Le Ny

Humans have come to rely on machines for reducing excessive information to manageable representations. But this reliance can be abused -- strategic machines might craft representations that manipulate their users. How can a user make good…

Machine Learning · Computer Science 2022-06-20 Vineet Nair , Ganesh Ghalme , Inbal Talgam-Cohen , Nir Rosenfeld

Algorithmic fairness in recommender systems requires close attention to the needs of a diverse set of stakeholders that may have competing interests. Previous work in this area has often been limited by fixed, single-objective definitions…

Information Retrieval · Computer Science 2024-10-08 Amanda Aird , Elena Štefancová , Cassidy All , Amy Voida , Martin Homola , Nicholas Mattei , Robin Burke
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