Fair Indivisible Payoffs through Shapley Value

📰 ArXiv cs.AI

Researchers propose using Shapley Value to fairly divide indivisible payoffs in coalitional games

advanced Published 2 Apr 2026

Action Steps

Define the grand coalition and its value as a natural number representing indivisible objects
Apply the Shapley Value method to calculate fair payoffs for each player
Consider the indivisibility of objects and adjust the payoff division accordingly
Evaluate the fairness of the resulting payoffs using metrics such as envy-freeness and efficiency

Who Needs to Know This

Data scientists and AI engineers working on machine learning models or coalition games can benefit from this research to ensure fair payoff division among players

Key Insight

💡 Shapley Value can be used to fairly divide indivisible payoffs in coalitional games

Key Takeaways

Researchers propose using Shapley Value to fairly divide indivisible payoffs in coalitional games

Full Article

Title: Fair Indivisible Payoffs through Shapley Value

Abstract:
arXiv:2510.24906v2 Announce Type: replace-cross Abstract: 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

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