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In a recent work, Moshkovitz [FOCS '14] presented a transformation on two-player games called "fortification", and gave an elementary proof of an (exponential decay) parallel repetition theorem for fortified two-player projection games. In…

Quantum Physics · Physics 2016-03-18 Mohammad Bavarian , Thomas Vidick , Henry Yuen

We study two-player general sum repeated finite games where the rewards of each player are generated from an unknown distribution. Our aim is to find the egalitarian bargaining solution (EBS) for the repeated game, which can lead to much…

Machine Learning · Computer Science 2019-06-05 Aristide Tossou , Christos Dimitrakakis , Jaroslaw Rzepecki , Katja Hofmann

We obtain quantitative estimates on the decay of the multiplayer optimal value under parallel repetition. In comparison to a previous work of the author in 2025 (arXiv: 2508.09380) which sought to generalize dependency-breaking and…

Quantum Physics · Physics 2026-05-12 Pete Rigas

This work proposes a novel distributed approach for computing a Nash equilibrium in convex games with merely monotone and restricted strongly monotone pseudo-gradients. By leveraging the idea of the centralized operator extrapolation method…

Optimization and Control · Mathematics 2025-07-18 Tatiana Tatarenko , Angelia Nedich

We consider two-player stochastic games played on a finite state space for an infinite number of rounds. The games are concurrent: in each round, the two players (player 1 and player 2) choose their moves independently and simultaneously;…

Computer Science and Game Theory · Computer Science 2012-01-04 Krishnendu Chatterjee

We conduct a comprehensive analysis of the discrete-time exponential-weights dynamic with a constant step size on all general-sum and symmetric $2 \times 2$ normal-form games, i.e. games with $2$ pure strategies per player, and where the…

Computer Science and Game Theory · Computer Science 2026-01-22 Guanghui Wang , Krishna Acharya , Lokranjan Lakshmikanthan , Juba Ziani , Vidya Muthukumar

This paper examines multiplayer symmetric constant-sum games with more than two players in a competitive setting, including examples like Mahjong, Poker, and various board and video games. In contrast to two-player zero-sum games,…

Machine Learning · Computer Science 2024-10-04 Jiawei Ge , Yuanhao Wang , Wenzhe Li , Chi Jin

We consider aggregative games with affine coupling constraints, where agents have partial information on the aggregate value and can only communicate with neighbouring agents. We propose a single-layer distributed algorithm that reaches a…

Optimization and Control · Mathematics 2020-08-14 Dian Gadjov , Lacra Pavel

We show that Optimistic Hedge -- a common variant of multiplicative-weights-updates with recency bias -- attains ${\rm poly}(\log T)$ regret in multi-player general-sum games. In particular, when every player of the game uses Optimistic…

Machine Learning · Computer Science 2023-01-26 Constantinos Daskalakis , Maxwell Fishelson , Noah Golowich

We consider eager-push epidemic dissemination in a complete graph. Time is divided into synchronous stages. In each stage, a source disseminates $\nu$ events. Each event is sent by the source, and forwarded by each node upon its first…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-21 Xavier Vilaca , Luis Rodrigues

In this article, we establish precise convergence rates of a general class of $N$-Player Stackelberg games to their mean field limits, which allows the response time delay of information, empirical distribution based interactions, and the…

Optimization and Control · Mathematics 2025-10-06 Alain Bensoussan , Ziyu Huang , Sheng Wang , Sheung Chi Phillip Yam

This work studies Nash equilibrium seeking for a class of stochastic aggregative games, where each player has an expectation-valued objective function depending on its local strategy and the aggregate of all players' strategies. We propose…

Optimization and Control · Mathematics 2022-05-17 Tongyu Wang , Peng Yi , Jie Chen

Proof-Number Search is a best-first search algorithm with many successful applications, especially in game solving. As large-scale computing clusters become increasingly accessible, parallelization is a natural way to accelerate…

Artificial Intelligence · Computer Science 2026-02-10 Tomáš Čížek , Martin Balko , Martin Schmid

We propose a general class of symmetric games called position-optimization games. Given a probability distribution $Q$ over a set of targets $\mathcal{Y}$, the $n$ players each choose a position in a space $\mathcal{X}$. A player's utility…

Computer Science and Game Theory · Computer Science 2026-02-18 Rafael Frongillo , Melody Hsu , Mary Monroe , Anish Thilagar

We consider concurrent games played on graphs. At every round of a game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety…

Computer Science and Game Theory · Computer Science 2008-09-25 Krishnendu Chatterjee , Luca de Alfaro , Thomas A. Henzinger

We prove that there exists a constant $\epsilon>0$ such that, assuming the Exponential Time Hypothesis for PPAD, computing an $\epsilon$-approximate Nash equilibrium in a two-player (nXn) game requires quasi-polynomial time,…

Computational Complexity · Computer Science 2016-08-31 Aviad Rubinstein

Infinitely repeated games can support cooperative outcomes that are not equilibria in the one-shot game. The idea is to make sure that any gains from deviating will be offset by retaliation in future rounds. However, this model of…

Computer Science and Game Theory · Computer Science 2024-06-04 Ratip Emin Berker , Vincent Conitzer

Most existing results about \emph{last-iterate convergence} of learning dynamics are limited to two-player zero-sum games, and only apply under rigid assumptions about what dynamics the players follow. In this paper we provide new results…

Computer Science and Game Theory · Computer Science 2022-03-24 Ioannis Anagnostides , Ioannis Panageas , Gabriele Farina , Tuomas Sandholm

Regret-based algorithms are highly efficient at finding approximate Nash equilibria in sequential games such as poker games. However, most regret-based algorithms, including counterfactual regret minimization (CFR) and its variants, rely on…

Machine Learning · Computer Science 2021-10-28 Chung-Wei Lee , Christian Kroer , Haipeng Luo

Imitating successful behavior is a natural and frequently applied approach to trust in when facing scenarios for which we have little or no experience upon which we can base our decision. In this paper, we consider such behavior in atomic…

Computer Science and Game Theory · Computer Science 2008-10-04 Heiner Ackermann , Petra Berenbrink , Simon Fischer , Martin Hoefer