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We study online fair allocation of $T$ sequentially arriving items among $n$ agents with heterogeneous preferences, with the objective of maximizing generalized-mean welfare, defined as the $p$-mean of agents' time-averaged utilities, with…

Computer Science and Game Theory · Computer Science 2026-02-12 Zongjun Yang , Rachitesh Kumar , Christian Kroer

No-regret learning has a long history of being closely connected to game theory. Recent works have devised uncoupled no-regret learning dynamics that, when adopted by all the players in normal-form games, converge to various equilibrium…

Computer Science and Game Theory · Computer Science 2024-04-24 Weichao Mao , Haoran Qiu , Chen Wang , Hubertus Franke , Zbigniew Kalbarczyk , Tamer Başar

Blackwell approachability, regret minimization and calibration are three criteria evaluating a strategy (or an algorithm) in different sequential decision problems, or repeated games between a player and Nature. Although they have at first…

Computer Science and Game Theory · Computer Science 2013-01-15 Vianney Perchet

While fictitious play is guaranteed to converge to Nash equilibrium in certain game classes, such as two-player zero-sum games, it is not guaranteed to converge in non-zero-sum and multiplayer games. We show that fictitious play in fact…

Computer Science and Game Theory · Computer Science 2024-07-30 Sam Ganzfried

We study a regret minimization problem with the existence of multiple best/near-optimal arms in the multi-armed bandit setting. We consider the case when the number of arms/actions is comparable or much larger than the time horizon, and…

Machine Learning · Statistics 2020-10-23 Yinglun Zhu , Robert Nowak

We study stochastic linear optimization problem with bandit feedback. The set of arms take values in an $N$-dimensional space and belong to a bounded polyhedron described by finitely many linear inequalities. We provide a lower bound for…

Machine Learning · Computer Science 2015-09-29 Manjesh K. Hanawal , Amir Leshem , Venkatesh Saligrama

We consider the interaction among agents engaging in a driving task and we model it as general-sum game. This class of games exhibits a plurality of different equilibria posing the issue of equilibrium selection. While selecting the most…

Pseudo-games are a natural and well-known generalization of normal-form games, in which the actions taken by each player affect not only the other players' payoffs, as in games, but also the other players' strategy sets. The solution…

Computer Science and Game Theory · Computer Science 2022-10-20 Denizalp Goktas , Amy Greenwald

We introduce the problem of regret minimization in Adversarial Dueling Bandits. As in classic Dueling Bandits, the learner has to repeatedly choose a pair of items and observe only a relative binary `win-loss' feedback for this pair, but…

Machine Learning · Computer Science 2020-10-29 Aadirupa Saha , Tomer Koren , Yishay Mansour

This paper studies two important signal processing aspects of equilibrium behavior in non-cooperative games arising in social networks, namely, reinforcement learning and detection of equilibrium play. The first part of the paper presents a…

Computer Science and Game Theory · Computer Science 2015-01-07 Omid Namvar Gharehshiran , William Hoiles , Vikram Krishnamurthy

We study a very general class of games --- multi-dimensional aggregative games --- which in particular generalize both anonymous games and weighted congestion games. For any such game that is also large, we solve the equilibrium selection…

Data Structures and Algorithms · Computer Science 2015-02-26 Rachel Cummings , Michael Kearns , Aaron Roth , Zhiwei Steven Wu

The minmax regret problem for combinatorial optimization under uncertainty can be viewed as a zero-sum game played between an optimizing player and an adversary, where the optimizing player selects a solution and the adversary selects costs…

Discrete Mathematics · Computer Science 2014-09-23 Andrew Mastin , Patrick Jaillet , Sang Chin

We study bandit learning in matching markets, where players and arms constitute the two market sides, and the players' utilities are linear in the arm contexts. In each round, new arms arrive with observable contexts. Then, the algorithm…

Machine Learning · Computer Science 2026-05-28 Shiyun Lin , Simon Mauras , Vianney Perchet , Nadav Merlis

We compare performance of the genetic algorithm and the counterfactual regret minimization algorithm in computing the near-equilibrium strategies in the simplified poker games. We focus on the von Neumann poker and the simplified version of…

Computer Science and Game Theory · Computer Science 2018-05-24 Mikhail Goykhman

We study voting games on binary issues, where voters hold an objective over the outcome of the collective decision and are allowed, before the vote takes place, to negotiate their voting strategy with the other participants. We analyse the…

Computer Science and Game Theory · Computer Science 2017-01-10 Umberto Grandi , Davide Grossi , Paolo Turrini

This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with a continuum of players, incorporating three types of perturbations. Such an equilibrium is shown to exist (in symmetric mixed…

Theoretical Economics · Economics 2021-05-06 Enxian Chen , Lei Qiao , Xiang Sun , Yeneng Sun

In the ultimatum game, the challenge is to explain why responders reject non-zero offers thereby defying classical rationality. Fairness and related notions have been the main explanations so far. We explain this rejection behavior via the…

Theoretical Economics · Economics 2023-11-16 Lida H. Aleksanyan , Armen E. Allahverdyan , Vardan G. Bardakhchyan

We show that in any $n$-player $m$-action normal-form game, we can obtain an approximate equilibrium by sampling any mixed-action equilibrium a small number of times. We study three types of equilibria: Nash, correlated and coarse…

Computer Science and Game Theory · Computer Science 2014-10-21 Yakov Babichenko , Siddharth Barman , Ron Peretz

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

Strategic-form min-max game theory examines the existence, multiplicity, selection of equilibria, and the worst-case computational complexity under perfect rationality. However, in many applications, games are drawn from an ensemble, and…

Computer Science and Game Theory · Computer Science 2026-02-17 Yuma Ichikawa
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