Fair Indivisible Payoffs through Shapley Value

Fuente: arXiv
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Auteurs principaux: Czarnecki, Mikołaj, Korniak, Michał, Skibski, Oskar, Skowron, Piotr
Format: Preprint
Publié: 2025
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author Czarnecki, Mikołaj
Korniak, Michał
Skibski, Oskar
Skowron, Piotr
author_facet Czarnecki, Mikołaj
Korniak, Michał
Skibski, Oskar
Skowron, Piotr
contents 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 exchanges, or top features contributing to the outcome of a machine learning model. The goal of this paper is to propose a fair method for dividing these objects among players. To achieve this, we define the indivisible Shapley value and study its properties. We demonstrate our proposed technique using three case studies, in particular, we use it to identify key regions of an image in the context of an image classification task.
format Preprint
id arxiv_https___arxiv_org_abs_2510_24906
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fair Indivisible Payoffs through Shapley Value
Czarnecki, Mikołaj
Korniak, Michał
Skibski, Oskar
Skowron, Piotr
Computer Science and Game Theory
Artificial Intelligence
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 exchanges, or top features contributing to the outcome of a machine learning model. The goal of this paper is to propose a fair method for dividing these objects among players. To achieve this, we define the indivisible Shapley value and study its properties. We demonstrate our proposed technique using three case studies, in particular, we use it to identify key regions of an image in the context of an image classification task.
title Fair Indivisible Payoffs through Shapley Value
topic Computer Science and Game Theory
Artificial Intelligence
url https://arxiv.org/abs/2510.24906