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Related papers: No-Regret Learning in Bayesian Games

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This paper investigates equilibrium computation and the price of anarchy for Bayesian games, which are the fundamental models of games with incomplete information. In normal-form games with complete information, it is known that efficiently…

Computer Science and Game Theory · Computer Science 2025-07-01 Kaito Fujii

A celebrated result in the interface of online learning and game theory guarantees that the repeated interaction of no-regret players leads to a coarse correlated equilibrium (CCE) -- a natural game-theoretic solution concept. Despite the…

Computer Science and Game Theory · Computer Science 2024-11-05 Ioannis Anagnostides , Alkis Kalavasis , Tuomas Sandholm

This paper studies the implementation of Bayes correlated equilibria in symmetric Bayesian games with nonatomic players, using direct information structures and obedient strategies. The main results demonstrate full implementation in a…

Theoretical Economics · Economics 2026-02-25 Frederic Koessler , Marco Scarsini , Tristan Tomala

The existence of simple uncoupled no-regret learning dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems. Specifically, it has been known for more than 20 years…

Computer Science and Game Theory · Computer Science 2021-05-28 Gabriele Farina , Andrea Celli , Alberto Marchesi , Nicola Gatti

The existence of simple, uncoupled no-regret dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems. Specifically, it has been known for more than 20 years that when…

Computer Science and Game Theory · Computer Science 2022-09-05 Andrea Celli , Alberto Marchesi , Gabriele Farina , Nicola Gatti

We introduce the notion of regularized Bayesian best response (RBBR) learning dynamic in heterogeneous population games. We obtain such a dynamic via perturbation by an arbitrary lower semicontinuous, strongly convex regularizer in Bayesian…

Optimization and Control · Mathematics 2023-03-13 Sayan Mukherjee , Souvik Roy

This paper examines the convergence of no-regret learning in games with continuous action sets. For concreteness, we focus on learning via "dual averaging", a widely used class of no-regret learning schemes where players take small steps…

Optimization and Control · Mathematics 2018-01-17 Panayotis Mertikopoulos , Zhengyuan Zhou

Computational tractability and social welfare (aka. efficiency) of equilibria are two fundamental but in general orthogonal considerations in algorithmic game theory. Nevertheless, we show that when (approximate) full efficiency can be…

Computer Science and Game Theory · Computer Science 2025-01-10 Ioannis Anagnostides , Tuomas Sandholm

We introduce a new paradigm for game theory -- Bayesian satisfaction. This novel approach is a synthesis of the idea of Bayesian rationality introduced by Aumann, and satisfaction games. The concept of Bayesian rationality for which, in…

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

No-regret learning dynamics play a central role in game theory, enabling decentralized convergence to equilibrium for concepts such as Coarse Correlated Equilibrium (CCE) or Correlated Equilibrium (CE). In this work, we improve the…

Computer Science and Game Theory · Computer Science 2025-11-05 Asrin Efe Yorulmaz , Tamer Başar

In this paper, we examine the long-run behavior of regularized, no-regret learning in finite games. A well-known result in the field states that the empirical frequencies of no-regret play converge to the game's set of coarse correlated…

Computer Science and Game Theory · Computer Science 2023-11-07 Victor Boone , Panayotis Mertikopoulos

Games are natural models for multi-agent machine learning settings, such as generative adversarial networks (GANs). The desirable outcomes from algorithmic interactions in these games are encoded as game theoretic equilibrium concepts, e.g.…

Computer Science and Game Theory · Computer Science 2022-02-25 Gabriel P. Andrade , Rafael Frongillo , Georgios Piliouras

We address the question of whether price of stability results (existence of equilibria with low social cost) are robust to incomplete information. We show that this is the case in potential games, if the underlying algorithmic social cost…

Computer Science and Game Theory · Computer Science 2015-03-13 Vasilis Syrgkanis

As quantum processors advance, the emergence of large-scale decentralized systems involving interacting quantum-enabled agents is on the horizon. Recent research efforts have explored quantum versions of Nash and correlated equilibria as…

Computer Science and Game Theory · Computer Science 2024-12-18 Wayne Lin , Georgios Piliouras , Ryann Sim , Antonios Varvitsiotis

A recent emerging trend in the literature on learning in games has been concerned with providing faster learning dynamics for correlated and coarse correlated equilibria in normal-form games. Much less is known about the significantly more…

Computer Science and Game Theory · Computer Science 2022-02-14 Ioannis Anagnostides , Gabriele Farina , Christian Kroer , Andrea Celli , Tuomas Sandholm

In game-theoretic learning, several agents are simultaneously following their individual interests, so the environment is non-stationary from each player's perspective. In this context, the performance of a learning algorithm is often…

Computer Science and Game Theory · Computer Science 2021-10-19 Yu-Guan Hsieh , Kimon Antonakopoulos , Panayotis Mertikopoulos

This paper examines the convergence of no-regret learning in Cournot games with continuous actions. Cournot games are the essential model for many socio-economic systems, where players compete by strategically setting their output quantity.…

Computer Science and Game Theory · Computer Science 2020-02-12 Yuanyuan Shi , Baosen Zhang

One of the most appealing aspects of the (coarse) correlated equilibrium concept is that natural dynamics quickly arrive at approximations of such equilibria, even in games with many players. In addition, there exist polynomial-time…

Computer Science and Game Theory · Computer Science 2015-04-24 Siddharth Barman , Katrina Ligett

Bayesian games model interactive decision-making where players have incomplete information -- e.g., regarding payoffs and private data on players' strategies and preferences -- and must actively reason and update their belief models (with…

Computer Science and Game Theory · Computer Science 2024-05-24 Zuyuan Zhang , Mahdi Imani , Tian Lan

We consider multi-population Bayesian games with a large number of players. Each player aims at minimizing a cost function that depends on this player's own action, the distribution of players' actions in all populations, and an unknown…

Computer Science and Game Theory · Computer Science 2023-09-06 Frederic Koessler , Marco Scarsini , Tristan Tomala
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