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We describe and develop a close relationship between two problems that have customarily been regarded as distinct: that of maximizing entropy, and that of minimizing worst-case expected loss. Using a formulation grounded in the equilibrium…

Statistics Theory · Mathematics 2007-06-13 Peter D. Grunwald , A. Philip Dawid

Evolutionary games between species are known to lead to intriguing spatio-temporal patterns in systems of diffusing agent. However, the role of inter-species interactions is hardly studied when agents are (self-)propelled, as is the case in…

Biological Physics · Physics 2021-10-18 Johanna Mayer , Michael Obermueller , Jonas Denk , Erwin Frey

Financial markets and more generally macro-economic models involve a large number of individuals interacting through variables such as prices resulting from the aggregate behavior of all the agents. Mean field games have been introduced to…

Optimization and Control · Mathematics 2021-07-12 René Carmona , Mathieu Laurière

Game Theory concepts have been successfully applied in a wide variety of domains over the past decade. Sports and games are one of the popular areas of game theory application owing to its merits and benefits in solving complex scenarios.…

Computer Science and Game Theory · Computer Science 2021-05-26 Ambareesh Ravi , Atharva Gokhale , Anchit Nagwekar

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

This paper generalizes L.S. Shapley's celebrated value allocation theory on coalition games by discovering and applying a fundamental connection between stochastic path integration driven by canonical time-reversible Markov chains and…

Probability · Mathematics 2022-01-04 Tongseok Lim

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

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

This paper introduces the shapr R package, a versatile tool for generating Shapley value-based prediction explanations for machine learning and statistical regression models. Moreover, the shaprpy Python library brings the core capabilities…

Machine Learning · Computer Science 2026-02-03 Martin Jullum , Lars Henry Berge Olsen , Jon Lachmann , Annabelle Redelmeier

The complex nature of artificial neural networks raises concerns on their reliability, trustworthiness, and fairness in real-world scenarios. The Shapley value -- a solution concept from game theory -- is one of the most popular explanation…

Machine Learning · Computer Science 2023-12-29 Jacopo Teneggi , Beepul Bharti , Yaniv Romano , Jeremias Sulam

The Shapley value is the solution concept in cooperative game theory that is most used in both theoretical as practical settings. Unfortunately, computing the Shapley value is computationally intractable in general. This paper focuses on…

Computer Science and Game Theory · Computer Science 2022-08-30 Tom C. van der Zanden , Hans L. Bodlaender , Herbert J. M. Hamers

The Shapley-Shubik index is a specialization of the Shapley value and is widely applied to evaluate the power distribution in committees drawing binary decisions. It was generalized to decisions with more than two levels of approval both in…

Computer Science and Game Theory · Computer Science 2020-10-09 Sascha Kurz , Issofa Moyouwou , Hilaire Touyem

In this paper we introduce polytopal stochastic games, an extension of two-player, zero-sum, turn-based stochastic games, in which we may have uncertainty over the transition probabilities. In these games the uncertainty over the…

Logic in Computer Science · Computer Science 2025-02-26 Pablo F. Castro , Pedro D'Argenio

This work uses game theory as a mathematical framework to address interaction modeling in multi-agent motion forecasting and control. Despite its interpretability, applying game theory to real-world robotics, like automated driving, faces…

Machine Learning · Computer Science 2023-12-05 Christopher Diehl , Tobias Klosek , Martin Krüger , Nils Murzyn , Timo Osterburg , Torsten Bertram

Game theory offers an interpretable mathematical framework for modeling multi-agent interactions. However, its applicability in real-world robotics applications is hindered by several challenges, such as unknown agents' preferences and…

Robotics · Computer Science 2023-10-17 Christopher Diehl , Tobias Klosek , Martin Krüger , Nils Murzyn , Torsten Bertram

This paper establishes a complete theoretical foundation for the Hodge-theoretic extension of the Shapley value introduced by Stern and Tettenhorst (2019). We show that a set of five axioms--efficiency, linearity, symmetry, a modified…

Optimization and Control · Mathematics 2025-10-14 Tongseok Lim

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

Electing a committee of size k from m alternatives (k < m) is an interesting problem under the multi-winner voting rules. However, very few committee selection rules found in the literature consider the coalitional possibilities among the…

Theoretical Economics · Economics 2023-08-08 Ritu Dutta , Rajnish Kumnar , Surajit Borkotokey

Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems facing uncertainty. Multi-objective stochastic games are natural…

Computational Complexity · Computer Science 2022-07-21 Tobias Winkler , Maximilian Weininger

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
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