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A valuation for a player in a game in extensive form is an assignment of numeric values to the players moves. The valuation reflects the desirability moves. We assume a myopic player, who chooses a move with the highest valuation.…

Machine Learning · Computer Science 2007-05-23 Philippe Jehiel , Dov Samet

Performance analysis of first-order algorithms with inexact oracles has gained recent attention due to various emerging applications in which obtaining exact gradients is impossible or computationally expensive. Previous research has…

Optimization and Control · Mathematics 2025-10-15 Yin Liu , Sam Davanloo Tajbakhsh

We propose a projected variational quantum extragradient (VQEG) framework for computing approximate Nash equilibria in two-player zero-sum matrix games. Mixed strategies are parameterized as Born distributions of parameterized quantum…

Systems and Control · Electrical Eng. & Systems 2026-04-21 Duong The Do , Matthew Aldridge , Duong Tung Nguyen

Extensive-Form Game (EFG) represents a fundamental model for analyzing sequential interactions among multiple agents and the primary challenge to solve it lies in mitigating sample complexity. Existing research indicated that Double Oracle…

Computer Science and Game Theory · Computer Science 2024-11-05 Xiaohang Tang , Chiyuan Wang , Chengdong Ma , Ilija Bogunovic , Stephen McAleer , Yaodong Yang

The state of the art in solving nonconvex nonsmooth games under uncertainty remains in its infancy. Existing studies primarily rely on stringent growth conditions or local convexity-like properties, making the development of alternative…

Optimization and Control · Mathematics 2026-03-09 Zhuoyu Xiao

We study the alternating gradient descent-ascent (AltGDA) algorithm in two-player zero-sum games. Alternating methods, where players take turns to update their strategies, have long been recognized as simple and practical approaches for…

Computer Science and Game Theory · Computer Science 2026-03-03 Tianlong Nan , Shuvomoy Das Gupta , Garud Iyengar , Christian Kroer

Self-play via online learning is one of the premier ways to solve large-scale two-player zero-sum games, both in theory and practice. Particularly popular algorithms include optimistic multiplicative weights update (OMWU) and optimistic…

Computer Science and Game Theory · Computer Science 2025-01-22 Yang Cai , Gabriele Farina , Julien Grand-Clément , Christian Kroer , Chung-Wei Lee , Haipeng Luo , Weiqiang Zheng

We tackle a fundamental problem in empirical game-theoretic analysis (EGTA), that of learning equilibria of simulation-based games. Such games cannot be described in analytical form; instead, a black-box simulator can be queried to obtain…

Computer Science and Game Theory · Computer Science 2019-06-03 Enrique Areyan Viqueira , Cyrus Cousins , Eli Upfal , Amy Greenwald

Nonzero-sum stochastic differential games with impulse controls offer a realistic and far-reaching modelling framework for applications within finance, energy markets, and other areas, but the difficulty in solving such problems has…

Numerical Analysis · Mathematics 2020-06-29 Diego Zabaljauregui

We introduce quantum XOR games, a model of two-player one-round games that extends the model of XOR games by allowing the referee's questions to the players to be quantum states. We give examples showing that quantum XOR games exhibit a…

Quantum Physics · Physics 2012-07-23 Oded Regev , Thomas Vidick

We study the application of iterative first-order methods to the problem of computing equilibria of large-scale two-player extensive-form games. First-order methods must typically be instantiated with a regularizer that serves as a…

Computer Science and Game Theory · Computer Science 2021-10-14 Gabriele Farina , Christian Kroer , Tuomas Sandholm

This paper resolves the open question of designing near-optimal algorithms for learning imperfect-information extensive-form games from bandit feedback. We present the first line of algorithms that require only…

Machine Learning · Computer Science 2023-04-04 Yu Bai , Chi Jin , Song Mei , Tiancheng Yu

In general, two-agent decision-making problems can be modeled as a two-player game, and a typical solution is to find a Nash equilibrium in such game. Counterfactual regret minimization (CFR) is a well-known method to find a Nash…

Computer Science and Game Theory · Computer Science 2020-12-07 Huale Li , Xuan Wang , Shuhan Qi , Jiajia Zhang , Yang Liu , Yulin Wu , Fengwei Jia

No-regret learning has emerged as a powerful tool for solving extensive-form games. This was facilitated by the counterfactual-regret minimization (CFR) framework, which relies on the instantiation of regret minimizers for simplexes at each…

Computer Science and Game Theory · Computer Science 2017-11-10 Gabriele Farina , Christian Kroer , Tuomas Sandholm

A considerable chasm has been looming for decades between theory and practice in zero-sum game solving through first-order methods. Although a convergence rate of $T^{-1}$ has long been established, the most effective paradigm in practice…

Computer Science and Game Theory · Computer Science 2026-02-18 Brian Hu Zhang , Ioannis Anagnostides , Tuomas Sandholm

We initiate the study of trembling-hand perfection in sequential (i.e., extensive-form) games with correlation. We introduce the extensive-form perfect correlated equilibrium (EFPCE) as a refinement of the classical extensive-form…

Computer Science and Game Theory · Computer Science 2020-12-14 Alberto Marchesi , Nicola Gatti

The proper equilibrium, introduced by Myerson (1978), is a classic refinement of the Nash equilibrium that has been referred to as the "mother of all refinements." For normal-form games, computing a proper equilibrium is known to be…

Computer Science and Game Theory · Computer Science 2026-02-11 Brian Hu Zhang , Ioannis Anagnostides , Kiriaki Fragkia , Maria-Florina Balcan , Tuomas Sandholm

We construct a saddle point in a class of zero-sum games between a stopper and a singular-controller. The underlying dynamics is a one-dimensional, time-homogeneous, singularly controlled diffusion taking values either on $\mathbb{R}$ or on…

Optimization and Control · Mathematics 2024-10-28 Andrea Bovo , Tiziano De Angelis

A celebrated connection in the interface of online learning and game theory establishes that players minimizing swap regret converge to correlated equilibria (CE) -- a seminal game-theoretic solution concept. Despite the long history of…

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

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
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