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Despite many distributed resource allocation (DRA) algorithms have been reported in literature, it is still unknown how to allocate the resource optimally over multiple interacting coalitions. One major challenge in solving such a problem…

Optimization and Control · Mathematics 2025-09-24 Jialing Zhou , Guanghui Wen , Yuezu Lv , Tao Yang , Guanrong Chen

This paper provides a novel solution to a task allocation problem, by which a group of agents decides on the assignment of a discrete set of tasks in a distributed manner. In this setting, heterogeneous agents have individual preferences…

Optimization and Control · Mathematics 2023-11-02 Nirabhra Mandal , Mohammad Khajenejad , Sonia Martínez

We consider multi-agent decision making, where each agent optimizes its cost function subject to constraints. Agents' actions belong to a compact convex Euclidean space and the agents' cost functions are coupled. We propose a distributed…

Optimization and Control · Mathematics 2016-12-01 Tatiana Tatarenko , Maryam Kamgarpour

Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products,…

Computer Science and Game Theory · Computer Science 2019-05-09 Omer Ben-Porat , Moshe Tennenholtz

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

This paper handles a kind of strategic game called potential games and develops a novel learning algorithm Payoff-based Inhomogeneous Partially Irrational Play (PIPIP). The present algorithm is based on Distributed Inhomogeneous Synchronous…

Systems and Control · Computer Science 2011-07-26 Tatsuhiko Goto , Takeshi Hatanaka , Masayuki Fujita

This paper introduces a novel payoff-based learning scheme for distributed optimization in repeatedly-played strategic-form games. Standard reinforcement-based learning exhibits several limitations with respect to their asymptotic…

Computer Science and Game Theory · Computer Science 2018-03-08 Georgios C. Chasparis

Distributed Nash equilibrium (NE) seeking problem for multi-coalition games has attracted increasing attention in recent years, but the research mainly focuses on the case without agreement demand within coalitions. This paper considers a…

Optimization and Control · Mathematics 2021-12-10 Jialing Zhou , Yuezu Lv , Guanghui Wen , Jinhu Lv , Dezhi Zheng

We study the open question of how players learn to play a social optimum pure-strategy Nash equilibrium (PSNE) through repeated interactions in general-sum coordination games. A social optimum of a game is the stable Pareto-optimal state…

Computer Science and Game Theory · Computer Science 2023-07-26 Duong Nguyen , Langford White , Hung Nguyen

Consider a set of agents who play a network game repeatedly. Agents may not know the network. They may even be unaware that they are interacting with other agents in a network. Possibly, they just understand that their payoffs depend on an…

Theoretical Economics · Economics 2022-07-26 Pierpaolo Battigalli , Fabrizio Panebianco , Paolo Pin

The Kelly or proportional allocation mechanism is a simple and efficient auction-based scheme that distributes an infinitely divisible resource proportionally to the agents bids. When agents are aware of the allocation rule, their…

Computer Science and Game Theory · Computer Science 2026-03-27 Younes Ben Mazziane , Cleque-Marlain Mboulou Moutoubi , Eitan Altman , Francesco De Pellegrini

The game-theoretic risk management framework put forth in the precursor work "Towards a Theory of Games with Payoffs that are Probability-Distributions" (arXiv:1506.07368 [q-fin.EC]) is herein extended by algorithmic details on how to…

General Economics · Economics 2020-04-10 Stefan Rass

The framework of uncoupled online learning in multiplayer games has made significant progress in recent years. In particular, the development of time-varying games has considerably expanded its modeling capabilities. However, current regret…

Computer Science and Game Theory · Computer Science 2025-08-18 Aymeric Capitaine , Etienne Boursier , Eric Moulines , Michael I. Jordan , Alain Durmus

A simple model for cooperation between "selfish" agents, which play an extended version of the Prisoner's Dilemma(PD) game, in which they use arbitrary payoffs, is presented and studied. A continuous variable, representing the probability…

Condensed Matter · Physics 2009-11-10 H. Fort

Organizations consist of individuals connected by their responsibilities, incentives, and reporting structure. These connections are aptly represented by a network, hierarchical or other, which is often used to divide tasks. A primary goal…

Computer Science and Game Theory · Computer Science 2017-03-09 Swaprava Nath , Balakrishnan , Narayanaswamy

Content creators compete for user attention. Their reach crucially depends on algorithmic choices made by developers on online platforms. To maximize exposure, many creators adapt strategically, as evidenced by examples like the sprawling…

Computer Science and Game Theory · Computer Science 2023-07-07 Jiri Hron , Karl Krauth , Michael I. Jordan , Niki Kilbertus , Sarah Dean

We study the problem of repeated play in a zero-sum game in which the payoff matrix may change, in a possibly adversarial fashion, on each round; we call these Online Matrix Games. Finding the Nash Equilibrium (NE) of a two player zero-sum…

Machine Learning · Computer Science 2020-04-06 Adrian Rivera Cardoso , Jacob Abernethy , He Wang , Huan Xu

A recent body of experimental literature has studied empirical game-theoretical analysis, in which we have partial knowledge of a game, consisting of observations of a subset of the pure-strategy profiles and their associated payoffs to…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Martin Gairing , Paul Goldberg , Rahul Savani

Consider $N$ players and $K$ games taking place simultaneously. Each of these games is modeled as a Tug-of-War (ToW) game where increasing the action of one player decreases the reward for all other players. Each player participates in only…

Computer Science and Game Theory · Computer Science 2026-04-14 Siddharth Chandak , Ilai Bistritz , Nicholas Bambos

In this paper, we study the distributed generalized Nash equilibrium seeking problem of non-cooperative games in dynamic environments. Each player in the game aims to minimize its own time-varying cost function subject to a local action…

Optimization and Control · Mathematics 2020-04-02 Kaihong Lu , Guangqi Li , Long Wang
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