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We study the 'no-dimension' analogue of Carath{\'e}odory's theorem in Banach spaces. We prove such a result together with its colorful version for uniformly smooth Banach spaces. It follows that uniform smoothness leads to a greedy…

泛函分析 · 数学 2019-07-09 G. M. Ivanov

We give a deterministic nearly-linear time algorithm for approximating any point inside a convex polytope with a sparse convex combination of the polytope's vertices. Our result provides a constructive proof for the Approximate…

数据结构与算法 · 计算机科学 2015-12-31 Vahab Mirrokni , Renato Paes Leme , Adrian Vladu , Sam Chiu-wai Wong

We present a new methodology for computing approximate Nash equilibria for two-person non-cooperative games based upon certain extensions and specializations of an existing optimization approach previously used for the derivation of fixed…

计算机科学与博弈论 · 计算机科学 2009-09-28 Haralampos Tsaknakis , Paul G. Spirakis

The approximate Carath\'eodory problem in general form is as follows: Given two symmetric convex bodies $P,Q \subseteq \mathbb{R}^m$, a parameter $k \in \mathbb{N}$ and $\mathbf{z} \in \textrm{conv}(X)$ with $X \subseteq P$, find…

度量几何 · 数学 2022-10-31 Victor Reis , Thomas Rothvoss

In Feinstein and Rudloff (2023), it was shown that the set of Nash equilibria for any non-cooperative $N$ player game coincides with the set of Pareto optimal points of a certain vector optimization problem with non-convex ordering cone. To…

最优化与控制 · 数学 2024-04-24 Zachary Feinstein , Niklas Hey , Birgit Rudloff

We investigate the complexity of computing approximate Nash equilibria in anonymous games. Our main algorithmic result is the following: For any $n$-player anonymous game with a bounded number of strategies and any constant $\delta>0$, an…

计算机科学与博弈论 · 计算机科学 2016-08-29 Yu Cheng , Ilias Diakonikolas , Alistair Stewart

The $\varepsilon$-well-supported Nash equilibrium is a strong notion of approximation of a Nash equilibrium, where no player has an incentive greater than $\varepsilon$ to deviate from any of the pure strategies that she uses in her mixed…

计算机科学与博弈论 · 计算机科学 2014-07-14 Artur Czumaj , Michail Fasoulakis , Marcin Jurdziński

Since the seminal PPAD-completeness result for computing a Nash equilibrium even in two-player games, an important line of research has focused on relaxations achievable in polynomial time. In this paper, we consider the notion of…

计算机科学与博弈论 · 计算机科学 2022-07-15 Argyrios Deligkas , Michail Fasoulakis , Evangelos Markakis

We prove that finding an $\epsilon$-approximate Nash equilibrium is PPAD-complete for constant $\epsilon$ and a particularly simple class of games: polymatrix, degree 3 graphical games, in which each player has only two actions. As…

计算机科学与博弈论 · 计算机科学 2016-09-14 Aviad Rubinstein

In recent work of Hazan and Krauthgamer (SICOMP 2011), it was shown that finding an $\eps$-approximate Nash equilibrium with near-optimal value in a two-player game is as hard as finding a hidden clique of size $O(\log n)$ in the random…

计算复杂性 · 计算机科学 2011-04-20 Per Austrin , Mark Braverman , Eden Chlamtac

Motivated by the fact that in many game-theoretic settings, the game analyzed is only an approximation to the game being played, in this work we analyze equilibrium computation for the broad and natural class of bimatrix games that are…

计算机科学与博弈论 · 计算机科学 2012-03-14 Maria-Florina Balcan , Mark Braverman

Nash equilibrium} (NE) can be stated as a formal theorem on a multilinear form, free of game theory terminology. On the other hand, inspired by this formalism, we state and prove a {\it multilinear minimax theorem}, a generalization of von…

计算机科学与博弈论 · 计算机科学 2024-01-01 Bahman Kalantari

The colorful Carath\'eodory theorem, proved by B\'ar\'any in 1982, states that given d+1 sets of points S_1,...,S_{d+1} in R^d, with each S_i containing 0 in its convex hull, there exists a subset T of the union of the S_i's containing 0 in…

离散数学 · 计算机科学 2016-10-03 Frédéric Meunier , Pauline Sarrabezolles

In this paper we consider the problem of computing an $\epsilon$-approximate Nash Equilibrium of a zero-sum game in a payoff matrix $A \in \mathbb{R}^{m \times n}$ with $O(1)$-bounded entries given access to a matrix-vector product oracle…

最优化与控制 · 数学 2025-09-05 Ishani Karmarkar , Liam O'Carroll , Aaron Sidford

This paper is about computing constrained approximate Nash equilibria in polymatrix games, which are succinctly represented many-player games defined by an interaction graph between the players. In a recent breakthrough, Rubinstein showed…

计算机科学与博弈论 · 计算机科学 2017-05-09 Argyrios Deligkas , John Fearnley , Rahul Savani

In this paper, we aim to design a distributed approximate algorithm for seeking Nash equilibria of an aggregative game. Due to the local set constraints of each player, projectionbased algorithms have been widely employed for solving such…

最优化与控制 · 数学 2021-08-30 Gehui Xu , Guanpu Chen , Hongsheng Qi , Yiguang Hong

We develop a quasi-polynomial time Las Vegas algorithm for approximating Nash equilibria in polymatrix games over trees, under a mild renormalizing assumption. Our result, in particular, leads to an expected polynomial-time algorithm for…

计算机科学与博弈论 · 计算机科学 2016-04-12 Siddharth Barman , Katrina Ligett , Georgios Piliouras

We study the deterministic and randomized query complexity of finding approximate equilibria in bimatrix games. We show that the deterministic query complexity of finding an $\epsilon$-Nash equilibrium when $\epsilon < \frac{1}{2}$ is…

计算机科学与博弈论 · 计算机科学 2014-02-13 John Fearnley , Rahul Savani

In an $\epsilon$-Nash equilibrium, a player can gain at most $\epsilon$ by unilaterally changing his behaviour. For two-player (bimatrix) games with payoffs in $[0,1]$, the best-known$\epsilon$ achievable in polynomial time is 0.3393. In…

计算机科学与博弈论 · 计算机科学 2014-10-02 Argyrios Deligkas , John Fearnley , Rahul Savani , Paul Spirakis

This work proposes a novel distributed approach for computing a Nash equilibrium in convex games with restricted strongly monotone pseudo-gradients. By leveraging the idea of the centralized operator extrapolation method presented in [4] to…

最优化与控制 · 数学 2023-10-25 Tatiana Tatarenko , Angelia Nedich
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