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In-depth studies of sociotechnical systems are largely limited to single instances. Network surveys are expensive, and platforms vary in important ways, from interface design, to social norms, to historical contingencies. With single…

Social and Information Networks · Computer Science 2018-11-06 Abigail Z. Jacobs

Team assembly is a problem that demands trade-offs between multiple fairness criteria and computational optimization. We focus on four criteria: (i) fair distribution of workloads within the team, (ii) fair distribution of skills and…

Databases · Computer Science 2023-06-27 Rodrigo Borges , Otto Sahlgrens , Sami Koivunen , Kostas Stefanidis , Thomas Olsson , Arto Laitinen

A population-based optimization algorithm was designed, inspired by two main thinking modes in philosophy, both based on dialectic concept and thesis-antithesis paradigm. They impose two different kinds of dialectics. Idealistic and…

Machine Learning · Computer Science 2017-09-05 S. Hossein Hosseini , Afshin Ebrahimi

Elections are the central institution of democratic processes, and often the elected body -- in either public or private governance -- is a committee of individuals. To ensure the legitimacy of elected bodies, the electoral processes should…

Computers and Society · Computer Science 2022-06-01 Florian Evéquoz , Johan Rochel , Vijay Keswani , L. Elisa Celis

We study a setting in which a community wishes to identify a strongly supported proposal from a space of alternatives, in order to change the status quo. We describe a deliberation process in which agents dynamically form coalitions around…

Multiagent Systems · Computer Science 2024-03-08 Edith Elkind , Davide Grossi , Ehud Shapiro , Nimrod Talmon

Viscous democracy is a generalization of liquid democracy, a social choice framework in which voters may transitively delegate their votes. In viscous democracy, a "viscosity" factor decreases the weight of a delegation the further it…

Physics and Society · Physics 2024-05-14 Ben Armstrong , Shiri Alouf-Heffetz , Nimrod Talmon

Sortition is the practice of delegating public decision-making to randomly selected panels. Recently, it has gained momentum worldwide through its use in citizens' assemblies, sparking growing interest within the computer science community.…

Computer Science and Game Theory · Computer Science 2025-05-20 Johannes Brustle , Simone Fioravanti , Tomasz Ponitka , Jeremy Vollen

As AI takes on a greater role in the modern world, it is essential to ensure that AI models can overcome decision uncertainty and remain aligned with human morality and interests. This research paper proposes a method for improving the…

Artificial Intelligence · Computer Science 2023-11-20 Thomas Forster , Jonathan Ouwerx , Shak Ragoler

We present a deliberation model where a group of individuals with heterogeneous preferences iteratively forms expert committees whose members are tasked with the updating of an exogenously given status quo change proposal. Every individual…

Theoretical Economics · Economics 2022-04-05 Dimitrios Karoukis

A common approach to aggregate classification estimates in an ensemble of decision trees is to either use voting or to average the probabilities for each class. The latter takes uncertainty into account, but not the reliability of the…

Machine Learning · Computer Science 2022-08-17 Florian Busch , Moritz Kulessa , Eneldo Loza Mencía , Hendrik Blockeel

Public opinion polling is usually done by random sampling from the entire population, treating individual opinions as independent. In the real world, individuals' opinions are often correlated, e.g., among friends in a social network. In…

Social and Information Networks · Computer Science 2016-11-28 Weiran Huang , Liang Li , Wei Chen

Optimization of expensive computer models with the help of Gaussian process emulators in now commonplace. However, when several (competing) objectives are considered, choosing an appropriate sampling strategy remains an open question. We…

Optimization and Control · Mathematics 2013-10-03 Victor Picheny

Distributed Constraint Optimization Problems (DCOPs) are a frequently used framework in which a set of independent agents choose values from their respective discrete domains to maximize their utility. Although this formulation is typically…

Multiagent Systems · Computer Science 2021-10-18 K. M. Merajul Arefin , Mashrur Rashik , Saaduddin Mahmud , Md. Mosaddek Khan

Mechanism design is concerned with settings where a policymaker (or social planner) faces the problem of aggregating the announced preferences of multiple agents into a collective (or social), system-wide decision. One of the most important…

Multiagent Systems · Computer Science 2020-03-02 Mohammad Ali Javidian , Pooyan Jamshidi , Marco Valtorta , Rasoul Ramezanian

Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervised learning problem, have been proposed recently. Finding good policies…

Machine Learning · Statistics 2009-12-30 Christos Dimitrakakis , Michail G. Lagoudakis

In participatory budgeting we are given a set of projects---each with a cost, an available budget, and a set of voters who in some form express their preferences over the projects. The goal is to select---based on voter preferences---a…

Multiagent Systems · Computer Science 2020-09-08 Piotr Skowron , Arkadii Slinko , Stanisław Szufa , Nimrod Talmon

The optimization of dynamic problems is both widespread and difficult. When conducting dynamic optimization, a balance between reinitialization and computational expense has to be found. There are multiple approaches to this. In parallel…

Neural and Evolutionary Computing · Computer Science 2014-01-21 Ronald Hochreiter , Christoph Waldhauser

Given the stated preferences of several people over a number of proposals regarding public policy initiatives, some of those proposals might be judged to be more ``divisive'' than others. When designing online participatory platforms to…

Computer Science and Game Theory · Computer Science 2026-01-01 Ulle Endriss

We consider a distributed voting problem with a set of agents that are partitioned into disjoint groups and a set of obnoxious alternatives. Agents and alternatives are represented by points in a metric space. The goal is to compute the…

Computer Science and Game Theory · Computer Science 2024-12-17 Alexandros A. Voudouris

The level of autonomy is increasing in systems spanning multiple domains, but these systems still experience failures. One way to mitigate the risk of failures is to integrate human oversight of the autonomous systems and rely on the human…

Artificial Intelligence · Computer Science 2022-09-28 Dylan M. Asmar , Mykel J. Kochenderfer
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