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Research on promoting cooperation among autonomous, self-regarding agents has often focused on the bi-objective optimisation problem: minimising the total incentive cost while maximising the frequency of cooperation. However, the optimal…

Small-world (SW) networks have been identified in many different fields. Topological coefficients like the clustering coefficient and the characteristic path length have been used in the past for a qualitative characterization of these…

Statistical Mechanics · Physics 2016-08-16 Tanya Araujo , R. Vilela Mendes , João Seixas

Yu and Zhang (2025) introduce a new method for defining trading mechanisms in market design and apply it to develop new mechanisms that achieve efficiency and fairness in various models. However, their assumption of strict preferences…

Theoretical Economics · Economics 2025-08-18 Jingsheng Yu , Jun Zhang

We initiate a novel direction in randomized social choice by proposing a new definition of agent utility for randomized outcomes. Each agent has a preference over all outcomes and a {\em quantile} parameter. Given a {\em lottery} over the…

Computer Science and Game Theory · Computer Science 2026-03-03 Ioannis Caragiannis , Fabian Frank , Sanjukta Roy

Social decision schemes (SDSs) map the voters' preferences over multiple alternatives to a probability distribution over these alternatives. In a seminal result, Gibbard (1977) has characterized the set of SDSs that are strategyproof with…

Computer Science and Game Theory · Computer Science 2025-08-25 Patrick Lederer

In social decision-making among strategic agents, a universal focus lies on the balance between social and individual interests. Socially efficient mechanisms are thus desirably designed to not only maximize the social welfare but also…

Computer Science and Game Theory · Computer Science 2024-07-29 Hirota Kinoshita , Takayuki Osogami , Kohei Miyaguchi

Based on the observation that many existing discrete choice models admit a welfare function of utilities whose gradient gives the choice probability vector, we propose a new representation of discrete choice model which we call the…

Optimization and Control · Mathematics 2015-03-09 Guiyun Feng , Xiaobo Li , Zizhuo Wang

We consider social welfare functions that satisfy Arrow's classic axioms of independence of irrelevant alternatives and Pareto optimality when the outcome space is the convex hull of some finite set of alternatives. Individual and…

Computer Science and Game Theory · Computer Science 2019-04-15 Florian Brandl , Felix Brandt

We propose social welfare optimization as a general paradigm for formalizing fairness in AI systems. We argue that optimization models allow formulation of a wide range of fairness criteria as social welfare functions, while enabling AI to…

Artificial Intelligence · Computer Science 2022-07-21 Violet Xinying Chen , J. N. Hooker

Given an initial resource allocation, where some agents may envy others or where a different distribution of resources might lead to higher social welfare, our goal is to improve the allocation without reassigning resources. We consider a…

Computer Science and Game Theory · Computer Science 2021-12-15 Robert Bredereck , Andrzej Kaczmarczyk , Junjie Luo , Rolf Niedermeier , Florian Sachse

Sociologists associate the spatial variation of crime within an urban setting, with the concept of collective efficacy. The collective efficacy of a neighborhood is defined as social cohesion among neighbors combined with their willingness…

Social and Information Networks · Computer Science 2021-02-16 Moniba Keymanesh , Saket Gurukar , Bethany Boettner , Christopher Browning , Catherine Calder , Srinivasan Parthasarathy

We study fairness in social choice settings under single-peaked preferences. Construction and characterization of social choice rules in the single-peaked domain has been extensively studied in prior works. In fact, in the single-peaked…

Computer Science and Game Theory · Computer Science 2022-07-19 Gogulapati Sreedurga , Soumyarup Sadhukhan , Souvik Roy , Yadati Narahari

In many real-world applications of reinforcement learning (RL), deployed policies have varied impacts on different stakeholders, creating challenges in reaching consensus on how to effectively aggregate their preferences. Generalized…

Machine Learning · Computer Science 2025-07-17 Cheol Woo Kim , Jai Moondra , Shresth Verma , Madeleine Pollack , Lingkai Kong , Milind Tambe , Swati Gupta

Random serial dictatorship (RSD) is a randomized assignment rule that - given a set of $n$ agents with strict preferences over $n$ houses - satisfies equal treatment of equals, ex post efficiency, and strategyproofness. For $n \le 3$,…

Theoretical Economics · Economics 2024-07-12 Felix Brandt , Matthias Greger , René Romen

I study dynamic random utility with finite choice sets and exogenous total menu variation, which I refer to as stochastic utility (SU). First, I characterize SU when each choice set has three elements. Next, I prove several mathematical…

Theoretical Economics · Economics 2022-06-22 Ricky Li

The notion of distortion in social choice problems has been defined to measure the loss in efficiency -- typically measured by the utilitarian social welfare, the sum of utilities of the participating agents -- due to having access only to…

Computer Science and Game Theory · Computer Science 2021-03-02 Elliot Anshelevich , Aris Filos-Ratsikas , Nisarg Shah , Alexandros A. Voudouris

Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and…

Computers and Society · Computer Science 2007-05-23 Ciro Cattuto , Vittorio Loreto , Luciano Pietronero

We axiomatically define a cardinal social inefficiency function, which, given a set of alternatives and individuals' vNM preferences over the alternatives, assigns a unique number -- the social inefficiency -- to each alternative. These…

Theoretical Economics · Economics 2026-02-10 Yannai A. Gonczarowski , Ella Segev

Recent literature on policy learning has primarily focused on regret bounds of the learned policy. We provide a new perspective by developing a unified semiparametric efficiency framework for policy learning, allowing for general treatments…

Econometrics · Economics 2026-02-10 Yue Fang , Geert Ridder , Haitian Xie

The efficient use of available resources is a key factor in achieving success on both personal and organizational levels. One of the crucial resources in knowledge economy is time. The ability to force others to adapt to our schedule even…

Multiagent Systems · Computer Science 2017-06-06 Michal Kakol , Radoslaw Nielek , Adam Wierzbicki