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In this paper we present a novel approach to optimise tactical and strategic decision making in football (soccer). We model the game of football as a multi-stage game which is made up from a Bayesian game to model the pre-match decisions…

Artificial Intelligence · Computer Science 2020-03-24 Ryan Beal , Georgios Chalkiadakis , Timothy J. Norman , Sarvapali D. Ramchurn

We study turn-based stochastic zero-sum games with lexicographic preferences over reachability and safety objectives. Stochastic games are standard models in control, verification, and synthesis of stochastic reactive systems that exhibit…

Computer Science and Game Theory · Computer Science 2022-07-21 Krishnendu Chatterjee , Joost-Pieter Katoen , Maximilian Weininger , Tobias Winkler

Trajectory guidance requires a leader robotic agent to assist a follower robotic agent to cooperatively reach the target destination. However, planning cooperation becomes difficult when the leader serves a family of different followers and…

Robotics · Computer Science 2024-03-19 Yuhan Zhao , Quanyan Zhu

In multi-agent problems requiring a high degree of cooperation, success often depends on the ability of the agents to adapt to each other's behavior. A natural solution concept in such settings is the Stackelberg equilibrium, in which the…

Machine Learning · Computer Science 2024-06-14 Robert Loftin , Mustafa Mert Çelikok , Herke van Hoof , Samuel Kaski , Frans A. Oliehoek

This paper studies a Stackelberg game wherein a sender (leader) attempts to shape the information of a less informed receiver (follower) who in turn takes an action that determines the payoff for both players. The sender chooses signals to…

Computer Science and Game Theory · Computer Science 2022-10-07 Reema Deori , Ankur A. Kulkarni

We study a stochastic game framework with dynamic set of players, for modeling and analyzing their computational investment strategies in distributed computing. Players obtain a certain reward for solving the problem or for providing their…

Computer Science and Game Theory · Computer Science 2019-11-19 Swapnil Dhamal , Walid Ben-Ameur , Tijani Chahed , Eitan Altman , Albert Sunny , Sudheer Poojary

In many multi-agent settings, participants can form teams to achieve collective outcomes that may far surpass their individual capabilities. Measuring the relative contributions of agents and allocating them shares of the reward that…

Machine Learning · Computer Science 2022-08-19 Daphne Cornelisse , Thomas Rood , Mateusz Malinowski , Yoram Bachrach , Tal Kachman

Device coordination in open spectrum systems is a challenging problem, particularly since users experience varying spectrum availability over time and location. In this paper, we propose a game theoretical approach that allows cognitive…

Computer Science and Game Theory · Computer Science 2016-11-18 Majed Haddad , Yezekael Hayel , Oussama Habachi

We present a new solution concept called evolutionarily stable Stackelberg equilibrium (SESS). We study the Stackelberg evolutionary game setting in which there is a single leading player and a symmetric population of followers. The leader…

Computer Science and Game Theory · Computer Science 2026-03-26 Sam Ganzfried

As energy demands surge across ICT infrastructures, service providers must engage users in sustainable practices while maintaining the Quality of Experience (QoE) at acceptable levels. In this paper, we introduce such an approach,…

Emerging Technologies · Computer Science 2026-01-30 Konstantinos Varsos , Adamantia Stamou , George D. Stamoulis , Vasillios A. Siris

Usually, to apply game-theoretic methods, we must specify utilities precisely, and we run the risk that the solutions we compute are not robust to errors in this specification. Ordinal games provide an attractive alternative: they require…

Computer Science and Game Theory · Computer Science 2024-07-11 Vincent Conitzer

Diffusion on complex networks is often modeled as a stochastic process. Yet, recent work on strategic diffusion emphasizes the decision power of agents and treats diffusion as a strategic problem. Here we study the computational aspects of…

Computational Complexity · Computer Science 2020-01-31 Marcin Waniek , Khaled Elbassioni , Flavio L. Pinheiro , Cesar A. Hidalgo , Aamena Alshamsi

This paper is concerned with a leader-follower stochastic differential game with asymmetric information, where the information available to the follower is based on some sub-$\sigma$-algebra of that available to the leader. Such kind of…

Optimization and Control · Mathematics 2015-09-15 Jingtao Shi , Guangchen Wang , Jie Xiong

Due to the large size of the training data, distributed learning approaches such as federated learning have gained attention recently. However, the convergence rate of distributed learning suffers from heterogeneous worker performance. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-09 Yunus Sarikaya , Ozgur Ercetin

We study the interaction between a network designer and an adversary over a dynamical network. The network consists of nodes performing continuous-time distributed averaging. The adversary strategically disconnects a set of links to prevent…

Systems and Control · Computer Science 2015-02-23 Ali Khanafer , Tamer Başar

Batch reinforcement learning (RL) defines the task of learning from a fixed batch of data lacking exhaustive exploration. Worst-case optimality algorithms, which calibrate a value-function model class from logged experience and perform some…

Machine Learning · Statistics 2023-10-03 Wenzhuo Zhou , Annie Qu

This paper investigates repeated win-lose coordination games (WLC-games). We analyse which protocols are optimal for these games covering both the worst case and average case scenarios, i,e., optimizing the guaranteed and expected…

Computer Science and Game Theory · Computer Science 2020-04-17 Antti Kuusisto , Raine Rönnholm

Existing methods for learning Stackelberg equilibria typically assume that the followers' (variational, generalized) Nash equilibrium is unique. However, in the presence of multiple equilibria, without a selection convention, the problem…

Optimization and Control · Mathematics 2026-04-30 Silvia Cianchi , Anibal Sanjab , Sergio Grammatico

We examine normal-form games in which players may \emph{pre-commit} to outcome-contingent transfers before choosing their actions. In the one-shot version of this model, Jackson and Wilkie showed that side contracting can backfire: even a…

Computer Science and Game Theory · Computer Science 2025-08-12 Ivan Geffner , Caspar Oesterheld , Vincent Conitzer

Cooperative game theory studies how to allocate the joint value generated by a set of players. These games are typically analyzed using the characteristic function form with transferable utility, which represents the value attainable by…

Theoretical Economics · Economics 2025-12-18 Ata Atay , Christian Trudeau
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