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Shapley value is a concept from game theory. Recently, it has been used for explaining complex models produced by machine learning techniques. Although the mathematical definition of Shapley value is straight-forward, the implication of…

Machine Learning · Computer Science 2020-08-13 Sisi Ma , Roshan Tourani

Artificial Neural Networks have shown impressive success in very different application cases. Choosing a proper network architecture is a critical decision for a network's success, usually done in a manual manner. As a straightforward…

Artificial Intelligence · Computer Science 2019-04-18 Julian Stier , Gabriele Gianini , Michael Granitzer , Konstantin Ziegler

Two straightforward methods to extend an assessment of individual elements to groups are to sum individual assessments or to treat the group as a single merged element and assess it accordingly. In this work, we analyze another natural…

Computer Science and Game Theory · Computer Science 2026-05-21 Piotr Kępczyński , Oskar Skibski

Every weighted tree corresponds naturally to a cooperative game that we call a "tree game"; it assigns to each subset of leaves the sum of the weights of the minimal subtree spanned by those leaves. In the context of phylogenetic trees, the…

Quantitative Methods · Quantitative Biology 2009-09-02 Claus-Jochen Haake , Akemi Kashiwada , Francis Edward Su

In allocation problems, a given set of goods are assigned to agents in such a way that the social welfare is maximised, that is, the largest possible global worth is achieved. When goods are indivisible, it is possible to use money…

Computer Science and Game Theory · Computer Science 2017-09-14 Francesco Lupia , Angelo Mendicelli , Andrea Ribichini , Francesco Scarcello , Marco Schaerf

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

We study the cost sharing problem for cooperative games in situations where the cost function $C$ is not available via oracle queries, but must instead be derived from data, represented as tuples $(S, C(S))$, for different subsets $S$ of…

Computer Science and Game Theory · Computer Science 2017-03-10 Eric Balkanski , Umar Syed , Sergei Vassilvitskii

Shapley values are great analytical tools in game theory to measure the importance of a player in a game. Due to their axiomatic and desirable properties such as efficiency, they have become popular for feature importance analysis in data…

Machine Learning · Computer Science 2020-10-26 Ramin Okhrati , Aldo Lipani

The Shapley value, originating from cooperative game theory, has been employed to define responsibility measures that quantify the contributions of database facts to obtaining a given query answer. For non-numeric queries, this is done by…

Databases · Computer Science 2026-01-19 Meghyn Bienvenu , Diego Figueira , Pierre Lafourcade

The Shapley value equals a player's contribution to the potential of a game. The potential is a most natural one-number summary of a game, which can be computed as the expected accumulated worth of a random partition of the players. This…

Theoretical Economics · Economics 2024-07-23 André Casajus , Yukihiko Funaki , Frank Huettner

We consider the problem of payoff division in indivisible coalitional games, where the value of the grand coalition is a natural number. This number represents a certain quantity of indivisible objects, such as parliamentary seats, kidney…

Computer Science and Game Theory · Computer Science 2026-04-02 Mikołaj Czarnecki , Michał Korniak , Oskar Skibski , Piotr Skowron

The Shapley value is widely used for data valuation in data markets. However, explaining the Shapley value of an owner in a data coalition is an unexplored and challenging task. To tackle this, we formulate the problem of finding the…

Computer Science and Game Theory · Computer Science 2025-07-03 Michelle Si , Jian Pei

The presence of artificial intelligence (AI) in our society is increasing, which brings with it the need to understand the behavior of AI mechanisms, including machine learning predictive algorithms fed with tabular data, text or images,…

Machine Learning · Statistics 2025-06-06 Pedro Delicado , Cristian Pachón-García

Measuring individual productivity (or equivalently distributing the overall productivity) in a network structure of workers displaying peer effects has been a subject of ongoing interest in many areas ranging from academia to industry. In…

Computer Science and Game Theory · Computer Science 2024-02-07 N. Allouch , Luis A. Guardiola , A. Meca

In many multi-agent settings, participants can form teams to achieve collective outcomes that may far surpass their individual capabilities. Measuring the relative contributions of agents and allocating them shares of the reward that…

Machine Learning · Computer Science 2022-08-19 Daphne Cornelisse , Thomas Rood , Mateusz Malinowski , Yoram Bachrach , Tal Kachman

Shapley values underlie one of the most popular model-agnostic methods within explainable artificial intelligence. These values are designed to attribute the difference between a model's prediction and an average baseline to the different…

Artificial Intelligence · Computer Science 2020-11-04 Tom Heskes , Evi Sijben , Ioan Gabriel Bucur , Tom Claassen

Feature attribution methods help make machine learning-based inference explainable by determining how much one or several features have contributed to a model's output. A particularly popular attribution method is based on the Shapley value…

Artificial Intelligence · Computer Science 2025-11-04 Filip Naudot , Tobias Sundqvist , Timotheus Kampik

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

The information decomposition problem requires an additive decomposition of the mutual information between the input and target variables into nonnegative terms. The recently introduced solution to this problem, Information Attribution,…

Information Theory · Computer Science 2022-07-13 Tomáš Kroupa , Sara Vannucci , Tomáš Votroubek

The Shapley value is one of the most widely used measures of feature importance partly as it measures a feature's average effect on a model's prediction. We introduce joint Shapley values, which directly extend Shapley's axioms and…

Machine Learning · Statistics 2022-02-11 Chris Harris , Richard Pymar , Colin Rowat