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In this paper, we study decentralized decision-making where agents optimize private objectives under incomplete information and imperfect public monitoring, in a non-cooperative setting. By shaping utilities-embedding shadow prices or…

Computer Science and Game Theory · Computer Science 2025-10-31 David Smith , Jie Dong , Yizhou Yang

SHAP (SHapley Additive exPlanations) values are a widely used method for local feature attribution in interpretable and explainable AI. We propose an efficient two-stage algorithm for computing SHAP values in both black-box setting and…

Machine Learning · Computer Science 2025-10-24 Ali Gorji , Andisheh Amrollahi , Andreas Krause

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

One of the goals of Explainable AI (XAI) is to determine which input components were relevant for a classifier decision. This is commonly know as saliency attribution. Characteristic functions (from cooperative game theory) are able to…

Machine Learning · Computer Science 2022-02-28 Stephan Wäldchen , Felix Huber , Sebastian Pokutta

In Explainable AI (XAI), Shapley values are a popular model-agnostic framework for explaining predictions made by complex machine learning models. The computation of Shapley values requires estimating non-trivial contribution functions…

Machine Learning · Computer Science 2026-01-27 Lars Henry Berge Olsen , Martin Jullum

We explore a broad class of values for cooperative games in characteristic function form, known as \emph{compromise values\/}. These values efficiently allocate payoffs by linearly combining well-specified upper and lower bounds on payoffs.…

Theoretical Economics · Economics 2025-10-15 Robert P. Gilles , René van den Brink

Cooperative game is a critical research area in the multi-agent reinforcement learning (MARL). Global reward game is a subclass of cooperative games, where all agents aim to maximize the global reward. Credit assignment is an important…

Machine Learning · Computer Science 2022-10-14 Jianhong Wang , Yuan Zhang , Tae-Kyun Kim , Yunjie Gu

Value factorisation is a useful technique for multi-agent reinforcement learning (MARL) in global reward game, however its underlying mechanism is not yet fully understood. This paper studies a theoretical framework for value factorisation…

Machine Learning · Computer Science 2023-01-10 Jianhong Wang , Yuan Zhang , Yunjie Gu , Tae-Kyun Kim

The core is a central solution concept in cooperative game theory, defined as the set of feasible allocations or payments such that no subset of agents has incentive to break away and form their own subgroup or coalition. However, it has…

We study equilibrium computation with extensive-form correlation in two-player turn-taking stochastic games. Our main results are two-fold: (1) We give an algorithm for computing a Stackelberg extensive-form correlated equilibrium (SEFCE),…

Computer Science and Game Theory · Computer Science 2024-12-24 Hanrui Zhang , Yu Cheng , Vincent Conitzer

Despite their ubiquitous use, Shapley value feature attributions can be misleading due to feature interaction in both model and data. We propose an alternative attribution approach, Shapley Sets, which awards value to sets of features.…

Machine Learning · Computer Science 2023-07-06 Torty Sivill , Peter Flach

This paper studies how to attain fairness in communication for omniscience, where a set of users exchange their observations of a discrete multiple random source to attain omniscience---the state that all users recover the entire source.…

Information Theory · Computer Science 2019-02-12 Ni Ding , Parastoo Sadeghi , David Smith , Thierry Rakotoarivelo

We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games, introduced in [19]. This class of games considers weighted congestion games in which Shapley values are used as an alternative (to…

Computer Science and Game Theory · Computer Science 2017-11-28 Matthias Feldotto , Martin Gairing , Grammateia Kotsialou , Alexander Skopalik

The Shapley value (SV) and Least core (LC) are classic methods in cooperative game theory for cost/profit sharing problems. Both methods have recently been proposed as a principled solution for data valuation tasks, i.e., quantifying the…

Machine Learning · Computer Science 2022-04-08 Tianhao Wang , Yu Yang , Ruoxi Jia

Shapley values, which were originally designed to assign attributions to individual players in coalition games, have become a commonly used approach in explainable machine learning to provide attributions to input features for black-box…

Machine Learning · Computer Science 2023-03-24 Che-Ping Tsai , Chih-Kuan Yeh , Pradeep Ravikumar

eXplainable Artificial Intelligence (XAI) is a sub-field of Artificial Intelligence (AI) that is at the forefront of AI research. In XAI, feature attribution methods produce explanations in the form of feature importance. People often use…

Artificial Intelligence · Computer Science 2022-02-09 Jamie Duell , Monika Seisenberger , Gert Aarts , Shangming Zhou , Xiuyi Fan

We study a game-theoretic model for pool formation in Proof of Stake blockchain protocols. In such systems, stakeholders can form pools as a means of obtaining regular rewards from participation in ledger maintenance, with the power of each…

Computer Science and Game Theory · Computer Science 2025-06-09 Aggelos Kiayias , Elias Koutsoupias , Evangelos Markakis , Panagiotis Tsamopoulos

One of the long-debated issues in coalitional game theory is how to extend the Shapley value to games with externalities (partition-function games). When externalities are present, not only can a player's marginal contribution - a central…

Computer Science and Game Theory · Computer Science 2013-08-29 Oskar Skibski , Tomasz P. Michalak , Michael Wooldridge

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

We introduce the notion of linearly representable games. Broadly speaking, these are TU games that can be described by as many parameters as the number of players, like weighted voting games, airport games, or bankruptcy games. We show that…

Computer Science and Game Theory · Computer Science 2024-11-11 Ferenc Illés