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Related papers: The Shapley Value in Knapsack Budgeted Games

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Cooperative interval game is a cooperative game in which every coalition gets assigned some closed real interval. This models uncertainty about how much the members of a coalition get for cooperating together. In this paper we study…

Computer Science and Game Theory · Computer Science 2018-11-12 Jan Bok

The computation of a solution concept of a cooperative game usually depends on values of all coalitions. However, in some applications, values of some of the coalitions might be unknown due to various reasons. We introduce a method to…

Computer Science and Game Theory · Computer Science 2022-12-12 Martin Černý

Motivated by the fact that the worth of a coalition may depend on the order in which agents arrive, Nowak and Radzik (1994) (NR) introduced cooperative games with generalized characteristic functions. We study such temporal cooperative…

Computer Science and Game Theory · Computer Science 2026-03-17 Ashwin Goyal , Drashthi Doshi , Swaprava Nath

Feature selection is a classical problem in statistics and machine learning, and it continues to remain an extremely challenging problem especially in the context of unknown non-linear relationships with dependent features. On the other…

Machine Learning · Statistics 2026-04-17 Chenghui Zheng , Garvesh Raskutti

Algorithmic fairness is an essential requirement as AI becomes integrated in society. In the case of social applications where AI distributes resources, algorithms often must make decisions that will benefit a subset of users, sometimes…

Artificial Intelligence · Computer Science 2023-02-22 Robert C. Gray , Jennifer Villareale , Thomas B. Fox , Diane H. Dallal , Santiago Ontañón , Danielle Arigo , Shahin Jabbari , Jichen Zhu

This paper introduces a measure of uncertainty in the determination of the Shapley value, illustrates it with examples, and studies some of its properties. The introduced measure of uncertainty quantifies random variations in a player's…

General Mathematics · Mathematics 2007-09-03 Vladislav Kargin

The Shapley value provides a principled framework for fairly distributing rewards among participants according to their individual contributions. While prior work has applied this concept to data valuation in machine learning, existing…

Computer Science and Game Theory · Computer Science 2026-01-22 Zhuofan Jia , Jian Pei

Researchers in explainable artificial intelligence have developed numerous methods for helping users understand the predictions of complex supervised learning models. By contrast, explaining the $\textit{uncertainty}$ of model outputs has…

Machine Learning · Statistics 2023-11-01 David S. Watson , Joshua O'Hara , Niek Tax , Richard Mudd , Ido Guy

The value and copyright of training data are crucial in the artificial intelligence industry. Service platforms should protect data providers' legitimate rights and fairly reward them for their contributions. Shapley value, a potent tool…

Machine Learning · Computer Science 2025-11-21 Haifeng Sun , Yu Xiong , Runze Wu , Xinyu Cai , Changjie Fan , Lan Zhang , Xiang-Yang Li

We investigate Gately's solution concept for cooperative games with transferable utilities. Gately's conception introduced a bargaining solution that minimises the maximal quantified ``propensity to disrupt'' the negotiation process of the…

Theoretical Economics · Economics 2023-07-11 Robert P. Gilles , Lina Mallozzi

Game-theoretic attribution techniques based on Shapley values are used to interpret black-box machine learning models, but their exact calculation is generally NP-hard, requiring approximation methods for non-trivial models. As the…

Machine Learning · Statistics 2022-02-04 Rory Mitchell , Joshua Cooper , Eibe Frank , Geoffrey Holmes

Shapley-related techniques have gained attention as both global and local interpretation tools because of their desirable properties. However, their computation using conditional expectations is computationally expensive. Approximation…

Machine Learning · Statistics 2022-07-13 Zhipu Zhou , Jie Chen , Linwei Hu

Automated data preparation pipeline construction is critical for machine learning success, yet existing methods suffer from two fundamental limitations: they treat pipeline construction as black-box optimization without quantifying…

Databases · Computer Science 2025-11-03 Jing Chang , Chang Liu , Jinbin Huang , Shuyuan Zheng , Rui Mao , Jianbin Qin

Shapley Values (SV) are widely used in explainable AI, but their estimation and interpretation can be challenging, leading to inaccurate inferences and explanations. As a starting point, we remind an invariance principle for SV and derive…

Machine Learning · Statistics 2023-06-01 Salim I. Amoukou , Nicolas J-B. Brunel , Tangi Salaün

Synthesis of finite-state controllers from high-level specifications in multi-agent systems can be reduced to solving multi-player concurrent games over finite graphs. The complexity of solving such games with qualitative objectives for…

Computer Science and Game Theory · Computer Science 2018-09-28 Shaull Almagor , Rajeev Alur , Suguman Bansal

Bayesian optimization (BO) with Gaussian processes (GP) has become an indispensable algorithm for black box optimization problems. Not without a dash of irony, BO is often considered a black box itself, lacking ways to provide reasons as to…

We consider game-theoretically secure distributed protocols for coalition games that approximate the Shapley value with small multiplicative error. Since all known existing approximation algorithms for the Shapley value are randomized, it…

Computer Science and Game Theory · Computer Science 2024-12-30 T-H. Hubert Chan , Qipeng Kuang , Quan Xue

Weighted timed games are zero-sum games played by two players on a timed automaton equipped with weights, where one player wants to minimise the accumulated weight while reaching a target. Weighted timed games are notoriously difficult and…

Computer Science and Game Theory · Computer Science 2018-12-05 Damien Busatto-Gaston , Benjamin Monmege , Pierre-Alain Reynier

Attribution scores can be applied in data management to quantify the contribution of individual items to conclusions from the data, as part of the explanation of what led to these conclusions. In Artificial Intelligence, Machine Learning,…

Databases · Computer Science 2024-01-15 Leopoldo Bertossi , Benny Kimelfeld , Ester Livshits , Mikaël Monet

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