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Related papers: Values of Games for Information Decomposition

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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

This paper studies cooperative games where coalitions are formed online and the value generated by the grand coalition must be irrevocably distributed among the players at each timestep. We investigate the fundamental issue of strategic…

Computer Science and Game Theory · Computer Science 2025-02-28 Haris Aziz , Yuhang Guo , Zhaohong Sun

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

False alarm is one of the main concerns in intensive care units and can result in care disruption, sleep deprivation, and insensitivity of care-givers to alarms. Several methods have been proposed to suppress the false alarm rate through…

Computer Vision and Pattern Recognition · Computer Science 2015-12-08 Fatemeh Afghah , Abolfazl Razi , Kayvan Najarian

Motivated by the fact that the worth of a coalition may depend on the order in which agents arrive, Nowak and Radzik (1994) (NR) introduced cooperative games with generalized characteristic functions. We study such temporal cooperative…

Computer Science and Game Theory · Computer Science 2026-03-17 Ashwin Goyal , Drashthi Doshi , Swaprava Nath

Power indices are essential in assessing the contribution and influence of individual agents in multi-agent systems, providing crucial insights into collaborative dynamics and decision-making processes. While invaluable, traditional…

Multiagent Systems · Computer Science 2025-03-12 Benjamin Kempinski , Tal Kachman

We address a noncooperative game problem in multi-controller system under delayed and asymmetric information structure. Under these conditions, the classical separation principle fails as estimation and control design become strongly…

Optimization and Control · Mathematics 2026-04-01 Xin Li , Qingyuan Qi , Kemi Ding

Variable selection or importance measurement of input variables to a machine learning model has become the focus of much research. It is no longer enough to have a good model, one also must explain its decisions. This is why there are so…

Machine Learning · Computer Science 2023-08-01 Vincent Lemaire , Fabrice Clérot , Marc Boullé

The price system is often said to economize on information, but economics has lacked a formal measure of how much information it saves. This paper develops such a measure. We construct a proof-theoretic framework for decentralized…

Theoretical Economics · Economics 2026-05-25 Shuige Liu

Motivated by the markets operating on fast time scales, we present a framework for online coalitional games with time-varying coalitional values and propose real-time payoff distribution mechanisms. Specifically, we design two online…

Systems and Control · Electrical Eng. & Systems 2023-01-31 Aitazaz Ali Raja , Sergio Grammatico

We propose a game-theoretic framework that incorporates both incomplete information and general ambiguity attitudes on factors external to all players. Our starting point is players' preferences on payoff-distribution vectors, essentially…

Economics · Quantitative Finance 2017-04-04 Jian Yang

Value function decomposition is becoming a popular rule of thumb for scaling up multi-agent reinforcement learning (MARL) in cooperative games. For such a decomposition rule to hold, the assumption of the individual-global max (IGM)…

Machine Learning · Computer Science 2022-02-17 Zehao Dou , Jakub Grudzien Kuba , Yaodong Yang

Boolean functions and their representation through logics, circuits, machine learning classifiers, or binary decision diagrams (BDDs) play a central role in the design and analysis of computing systems. Quantifying the relative impact of…

Computer Science and Game Theory · Computer Science 2023-05-16 Hans Harder , Simon Jantsch , Christel Baier , Clemens Dubslaff

We investigate Gately's solution concept for cooperative games with transferable utilities. Gately's conception introduced a bargaining solution that minimises the maximal quantified ``propensity to disrupt'' the negotiation process of the…

Theoretical Economics · Economics 2023-07-11 Robert P. Gilles , Lina Mallozzi

We propose in this paper a coinvestment plan between several stakeholders of different types, namely a physical network owner, operating network nodes, e.g. a network operator or a tower company, and a set of service providers willing to…

Computer Science and Game Theory · Computer Science 2022-10-04 Rosario Patanè , Andrea Araldo , Tijani Chahed , Diego Kiedanski , Daniel Kofman

Standard decision frameworks address uncertainty about facts but assume fixed options and values. We extend the Jeffrey-Bolker framework to model refinements in values and prove a value-of-information theorem for axiological refinement. In…

Artificial Intelligence · Computer Science 2026-04-15 Alex John London , Aydin Mohseni

Zero-sum stochastic games provide a rich model for competitive decision making. However, under general forms of state uncertainty as considered in the Partially Observable Stochastic Game (POSG), such decision making problems are still not…

Artificial Intelligence · Computer Science 2016-06-23 Auke J. Wiggers , Frans A. Oliehoek , Diederik M. Roijers

The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of…

Systems and Control · Computer Science 2015-03-19 Tamer Basar , Quanyan Zhu

We study instancewise feature importance scoring as a method for model interpretation. Any such method yields, for each predicted instance, a vector of importance scores associated with the feature vector. Methods based on the Shapley score…

Machine Learning · Computer Science 2018-08-09 Jianbo Chen , Le Song , Martin J. Wainwright , Michael I. Jordan

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