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Collaborative machine learning (ML) is an appealing paradigm to build high-quality ML models by training on the aggregated data from many parties. However, these parties are only willing to share their data when given enough incentives,…

Machine Learning · Computer Science 2020-10-27 Rachael Hwee Ling Sim , Yehong Zhang , Mun Choon Chan , Bryan Kian Hsiang Low

The ubiquity of social platforms has reshaped the way information, behaviors, and advertisements diffuse across networks, with influence propagation often initiated by a small set of ``seed'' users. While much of the literature emphasizes…

Social and Information Networks · Computer Science 2026-05-28 Fangzhu Shen , Amir Gilad , Sudeepa Roy

Following the work of Lloyd Shapley on the Shapley value, and tangentially the work of Guillermo Owen, we offer an alternative non-probabilistic formulation of part of the work of Robert J. Weber in his 1978 paper "Probabilistic values for…

Theoretical Economics · Economics 2019-05-13 Jacob North Clark , Stephen Montgomery-Smith

We propose the following question: what game-like interactive system would provide a good environment for measuring the impact and success of a co-creative, cooperative agent? Creativity is often formulated in terms of novelty, value,…

Artificial Intelligence · Computer Science 2018-09-27 Rodrigo Canaan , Stefan Menzel , Julian Togelius , Andy Nealen

Shapley value is a classic notion from game theory, historically used to quantify the contributions of individuals within groups, and more recently applied to assign values to data points when training machine learning models. Despite its…

Machine Learning · Computer Science 2020-02-28 Amirata Ghorbani , Michael P. Kim , James Zou

Traditionally social sciences are interested in structuring people in multiple groups based on their individual preferences. This pa- per suggests an approach to this problem in the framework of a non- cooperative game theory. Definition of…

Optimization and Control · Mathematics 2017-05-02 Dmitry Levando

We propose the study of computing the Shapley value for a new class of cooperative games that we call budgeted games, and investigate in particular knapsack budgeted games, a version modeled after the classical knapsack problem. In these…

Computer Science and Game Theory · Computer Science 2014-09-19 Smriti Bhagat , Anthony Kim , S. Muthukrishnan , Udi Weinsberg

Multi-agent reinforcement learning is an area of rapid advancement in artificial intelligence and machine learning. One of the important questions to be answered is how to conduct credit assignment in a multi-agent system. There have been…

Multiagent Systems · Computer Science 2024-02-26 Jianhong Wang

A wireless relay network (WRN) has recently emerged as an effective way to increase communication capacity and extend a coverage area with a low cost. In the WRN, multiple service providers (SPs) can cooperate to share their resources…

Networking and Internet Architecture · Computer Science 2016-11-15 Xiao Lu , Ping Wang , Dusit Niyato

This paper is about the possible negative impact of excessive collaboration on the performance of top employees. With the rise of participatory culture and developments in communications technology, management practices require greater…

Applications · Statistics 2020-04-29 Anna Velyka , Marco Guerzoni

Cooperation is a fundamental social mechanism, whose effects on human performance have been investigated in several environments. Online games are modern-days natural settings in which cooperation strongly affects human behavior. Every day,…

Social and Information Networks · Computer Science 2019-08-22 Anna Sapienza , Palash Goyal , Emilio Ferrara

Cooperative game theory has become a cornerstone of post-hoc interpretability in machine learning, largely through the use of Shapley values. Yet, despite their widespread adoption, Shapley-based methods often rest on axiomatic…

Machine Learning · Statistics 2025-06-18 Marouane Il Idrissi , Agathe Fernandes Machado , Arthur Charpentier

In this paper, we address the problem of fair sharing of the total value of a crowd-sourced network system between major participants (founders) and minor participants (crowd) using cooperative game theory. Shapley allocation is regarded as…

Computer Science and Game Theory · Computer Science 2023-05-23 Mishal Assif P K , William Kennedy , Iraj Saniee

We introduce and analyze a novel family of power indices tailored for sharing networks in technological markets, where firms operate competitively within, but not across, distinct industrial sectors. In these settings, inter-firm…

Theoretical Economics · Economics 2025-07-18 Michele Aleandri , Francesco Ciardiello , Andrea Di Liddo

Punishment as a mechanism for promoting cooperation has been studied extensively for more than two decades, but its effectiveness remains a matter of dispute. Here, we examine how punishment's impact varies across cooperative settings…

General Economics · Economics 2025-08-26 Mohammed Alsobay , David G. Rand , Duncan J. Watts , Abdullah Almaatouq

This article shows how coworker performance affects individual performance evaluation in a teamwork setting at the workplace. We use high-quality data on football matches to measure an important component of individual performance, shooting…

General Economics · Economics 2024-03-25 Enzo Brox , Michael Lechner

In this paper, a novel framework for normative modeling of the spectrum sensing and sharing problem in cognitive radios (CRs) as a transferable utility (TU) cooperative game is proposed. Secondary users (SUs) jointly sense the spectrum and…

Computer Science and Game Theory · Computer Science 2011-12-08 Jayaprakash Rajasekharan , Jan Eriksson , Visa Koivunen

We study a cooperative game setting where the grand coalition may change since the initial players can invite more players. We focus on monotone games, i.e., adding more players to the grand coalition is not harmful. We model the invitation…

Computer Science and Game Theory · Computer Science 2022-01-03 Yao Zhang , Dengji Zhao

Game theory has been one of the most successful quantitative concepts to describe social interactions, their strategical aspects, and outcomes. Among the payoff matrix quantifying the result of a social interaction, the interaction…

Physics and Society · Physics 2017-11-22 Wenjian Yu , Dirk Helbing

We introduce a game-theoretic approach to the study of recommendation systems with strategic content providers. Such systems should be fair and stable. Showing that traditional approaches fail to satisfy these requirements, we propose the…

Computer Science and Game Theory · Computer Science 2018-10-19 Omer Ben-Porat , Moshe Tennenholtz