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We argue that the existing regret matchings for Nash equilibrium approximation conduct "jumpy" strategy updating when the probabilities of future plays are set to be proportional to positive regret measures. We propose a geometrical regret…

Computer Science and Game Theory · Computer Science 2020-01-24 Sizhong Lan

This paper explores aggregative games in a network of general linear systems subject to external disturbances. To deal with external disturbances, distributed strategy-updating rules based on internal model are proposed for the case with…

Optimization and Control · Mathematics 2024-10-28 Xin Cai , Feng Xiao , Bo Wei , Mei Yu , Fang Fang

In competitive multi-player interactions, simultaneous optimality is a key requirement for establishing strategic equilibria. This property is explicit when the game-theoretic equilibrium is the simultaneously optimal solution of coupled…

Computer Science and Game Theory · Computer Science 2024-04-04 Sarah H. Q. Li , Yue Yu , Florian Dörfler , John Lygeros

This paper examines the long-run behavior of learning with bandit feedback in non-cooperative concave games. The bandit framework accounts for extremely low-information environments where the agents may not even know they are playing a…

Computer Science and Game Theory · Computer Science 2018-10-05 Mario Bravo , David S. Leslie , Panayotis Mertikopoulos

We present a new class of vertex cover and set cover games. The price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs -- in…

Computer Science and Game Theory · Computer Science 2012-03-02 Georgios Piliouras , Tomas Valla , Laszlo A. Vegh

We consider seeking generalized Nash equilibria (GNE) for noncooperative games with coupled nonlinear constraints over networks. We first revisit a well-known gradientplay dynamics from a passivity-based perspective, and address that the…

Optimization and Control · Mathematics 2024-08-23 Weijian Li , Lacra Pavel

We study the repeated congestion game, in which multiple populations of players share resources, and make, at each iteration, a decentralized decision on which resources to utilize. We investigate the following question: given a model of…

Machine Learning · Computer Science 2014-08-04 Walid Krichene , Benjamin Drighès , Alexandre M. Bayen

Different types of dynamics have been studied in repeated game play, and one of them which has received much attention recently consists of those based on "no-regret" algorithms from the area of machine learning. It is known that dynamics…

Computer Science and Game Theory · Computer Science 2016-10-14 Po-An Chen , Chi-Jen Lu

We consider two classes of constrained finite state-action stochastic games. First, we consider a two player nonzero sum single controller constrained stochastic game with both average and discounted cost criterion. We consider the same…

Optimization and Control · Mathematics 2012-06-11 Vikas Vikram Singh , N. Hemachandra

No-regret self-play learning dynamics have become one of the premier ways to solve large-scale games in practice. Accelerating their convergence via improving the regret of the players over the naive $O(\sqrt{T})$ bound after $T$ rounds has…

Machine Learning · Computer Science 2025-02-26 Shinji Ito , Haipeng Luo , Taira Tsuchiya , Yue Wu

The design of Nash equilibrium seeking strategies for games in which the involved players are of second-order integrator-type dynamics is investigated in this paper. Noticing that velocity signals are usually noisy or not available for…

Optimization and Control · Mathematics 2020-06-18 Maojiao Ye , Jizhao Yin , Le Yin

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

The Nash equilibrium is an important benchmark for behaviour in systems of strategic autonomous agents. Polymatrix games are a succinct and expressive representation of multiplayer games that model pairwise interactions between players. The…

Computer Science and Game Theory · Computer Science 2016-03-17 Argyrios Deligkas , John Fearnley , Tobenna Peter Igwe , Rahul Savani

We consider the problem of computing mixed Nash equilibria of two-player zero-sum games with continuous sets of pure strategies and with first-order access to the payoff function. This problem arises for example in game-theory-inspired…

Optimization and Control · Mathematics 2025-09-04 Guillaume Wang , Lénaïc Chizat

Motivated by the scarcity of accurate payoff feedback in practical applications of game theory, we examine a class of learning dynamics where players adjust their choices based on past payoff observations that are subject to noise and…

Optimization and Control · Mathematics 2016-06-03 Mario Bravo , Panayotis Mertikopoulos

Research in adversarial learning follows a cat and mouse game between attackers and defenders where attacks are proposed, they are mitigated by new defenses, and subsequently new attacks are proposed that break earlier defenses, and so on.…

Machine Learning · Computer Science 2020-11-13 Ambar Pal , René Vidal

We introduce a novel class of Nash equilibrium seeking dynamics for non-cooperative games with a finite number of players, where the convergence to the Nash equilibrium is bounded by a KL function with a settling time that can be upper…

Optimization and Control · Mathematics 2020-12-25 Jorge I. Poveda , Miroslav Krstic , Tamer Basar

Several notions of game enjoy a Nash-like notion of equilibrium without guarantee of existence. There are different ways of weakening a definition of Nash-like equilibrium in order to guarantee the existence of a weakened equilibrium.…

Computer Science and Game Theory · Computer Science 2007-12-11 Stéphane Le Roux

Driven by recent successes in two-player, zero-sum game solving and playing, artificial intelligence work on games has increasingly focused on algorithms that produce equilibrium-based strategies. However, this approach has been less…

Computer Science and Game Theory · Computer Science 2022-06-24 Dustin Morrill , Ryan D'Orazio , Reca Sarfati , Marc Lanctot , James R. Wright , Amy Greenwald , Michael Bowling

This paper investigates the privacy-preserving distributed Nash equilibrium seeking problem for aggregative games. A novel differential privacy mechanism is designed by incorporating stochastic event-triggering with stochastic quantization,…

Optimization and Control · Mathematics 2026-05-27 Qingtan Meng , Qian Ma
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