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A fundamental shortcoming of the concept of Nash equilibrium is its computational intractability: approximating Nash equilibria in normal-form games is PPAD-hard. In this paper, inspired by the ideas of smoothed analysis, we introduce a…

Computer Science and Game Theory · Computer Science 2024-07-23 Constantinos Daskalakis , Noah Golowich , Nika Haghtalab , Abhishek Shetty

In game theory, players have continuous expected payoff functions and can use fixed point theorems to locate equilibria. This optimization method requires that players adopt a particular type of probability measure space. Here, we introduce…

Optimization and Control · Mathematics 2007-05-23 Michael J. Gagen , Kae Nemoto

We consider infinite duration alternating move games. These games were previously studied by Roth, Balcan, Kalai and Mansour. They presented an FPTAS for computing an approximated equilibrium, and conjectured that there is a polynomial…

Computer Science and Game Theory · Computer Science 2013-04-25 Yaron Velner

In order to find Nash-equilibria for two-player zero-sum games where each player plays combinatorial objects like spanning trees, matchings etc, we consider two online learning algorithms: the online mirror descent (OMD) algorithm and the…

Machine Learning · Computer Science 2016-03-03 Swati Gupta , Michel Goemans , Patrick Jaillet

We propose a new iteration scheme, the Cauchy-Simplex, to optimize convex problems over the probability simplex $\{w\in\mathbb{R}^n\ |\ \sum_i w_i=1\ \textrm{and}\ w_i\geq0\}$. Specifically, we map the simplex to the positive quadrant of a…

Optimization and Control · Mathematics 2025-05-22 James Chok , Geoffrey M. Vasil

Adversarial multiplayer games are an important object of study in multiagent learning. In particular, polymatrix zero-sum games are a multiplayer setting where Nash equilibria are known to be efficiently computable. Towards understanding…

Computer Science and Game Theory · Computer Science 2026-04-13 Alexandros Hollender , Gilbert Maystre , Sai Ganesh Nagarajan

We tackle the problem of learning equilibria in simulation-based games. In such games, the players' utility functions cannot be described analytically, as they are given through a black-box simulator that can be queried to obtain noisy…

Computer Science and Game Theory · Computer Science 2020-02-26 Alberto Marchesi , Francesco Trovò , Nicola Gatti

Game theory finds nowadays a broad range of applications in engineering and machine learning. However, in a derivative-free, expensive black-box context, very few algorithmic solutions are available to find game equilibria. Here, we propose…

Machine Learning · Statistics 2018-02-28 Victor Picheny , Mickael Binois , Abderrahmane Habbal

Finding a counterfeit coin with the different weight from a set of visually identical coin using a balance, usually a two-armed balance, known as the balance question, is an intersting and inspiring question. Its variants involve…

Information Theory · Computer Science 2020-07-28 Fangqi Li

We consider a general class of Bayesian Games where each players utility depends on his type (possibly multidimensional) and on the strategy profile and where players' types are distributed independently. We show that if their full…

Computer Science and Game Theory · Computer Science 2012-03-26 Vasilis Syrgkanis

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

We study the computation of equilibria of anonymous games, via algorithms that may proceed via a sequence of adaptive queries to the game's payoff function, assumed to be unknown initially. The general topic we consider is \emph{query…

Computer Science and Game Theory · Computer Science 2016-05-06 Paul W. Goldberg , Stefano Turchetta

We address the numerical approximation of Mean Field Games with local couplings. For power-like Hamiltonians, we consider both unconstrained and constrained stationary systems with density constraints in order to model hard congestion…

Optimization and Control · Mathematics 2019-02-08 L. M. Briceño-Arias , D. Kalise , F. J. Silva

In this work, we investigate a security game between an attacker and a defender, originally proposed in \cite{emadi2019security}. As is well known, the combinatorial nature of security games leads to a large cost matrix. Therefore,…

Computer Science and Game Theory · Computer Science 2020-07-30 HAmid Emadi , Sourabh Bhattacharya

Decision trees are one of the most fundamental computational models for computing Boolean functions $f : \{0, 1\}^n \mapsto \{0, 1\}$. It is well-known that the depth and size of decision trees are closely related to time and number of…

Computational Complexity · Computer Science 2025-01-03 Deepu Benson , Balagopal Komarath , Jayalal Sarma , Nalli Sai Soumya

In this work, we propose, for the first time, a reinforcement learning framework specifically designed for zero-sum linear-quadratic stochastic differential games. This approach offers a generalized solution for scenarios in which accurate…

Optimization and Control · Mathematics 2026-02-10 Yiyuan Wang

Rademacher complexity is often used to characterize the learnability of a hypothesis class and is known to be related to the class size. We leverage this observation and introduce a new technique for estimating the size of an arbitrary…

Machine Learning · Computer Science 2018-01-30 Jonathan Kuck , Ashish Sabharwal , Stefano Ermon

This paper develops a unified framework for testing monotonicity of Bayesian Nash equilibrium strategies in unobserved types in games of incomplete information. We show that, under symmetric independent private types, monotonicity of…

Econometrics · Economics 2026-04-09 Yu-Chin Hsu , Tong Li , Chu-An Liu , Hidenori Takahashi

We study strategic games on weighted directed graphs, in which the payoff of a player is defined as the sum of the weights on the edges from players who chose the same strategy, augmented by a fixed non-negative integer bonus for picking a…

Computer Science and Game Theory · Computer Science 2021-03-15 Krzysztof R. Apt , Sunil Simon , Dominik Wojtczak

Lipschitz games, in which there is a limit $\lambda$ (the Lipschitz value of the game) on how much a player's payoffs may change when some other player deviates, were introduced about 10 years ago by Azrieli and Shmaya. They showed via the…

Computer Science and Game Theory · Computer Science 2022-07-21 Paul W. Goldberg , Matthew J. Katzman
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