Swim till You Sink: Computing the Limit of a Game

Fuente: arXiv
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Main Authors: Hakim, Rashida, Milionis, Jason, Papadimitriou, Christos, Piliouras, Georgios
Format: Preprint
Published: 2024
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author Hakim, Rashida
Milionis, Jason
Papadimitriou, Christos
Piliouras, Georgios
author_facet Hakim, Rashida
Milionis, Jason
Papadimitriou, Christos
Piliouras, Georgios
contents During 2023, two interesting results were proven about the limit behavior of game dynamics: First, it was shown that there is a game for which no dynamics converges to the Nash equilibria. Second, it was shown that the sink equilibria of a game adequately capture the limit behavior of natural game dynamics. These two results have created a need and opportunity to articulate a principled computational theory of the meaning of the game that is based on game dynamics. Given any game in normal form, and any prior distribution of play, we study the problem of computing the asymptotic behavior of a class of natural dynamics called the noisy replicator dynamics as a limit distribution over the sink equilibria of the game. When the prior distribution has pure strategy support, we prove this distribution can be computed efficiently, in near-linear time to the size of the best-response graph. When the distribution can be sampled -- for example, if it is the uniform distribution over all mixed strategy profiles -- we show through experiments that the limit distribution of reasonably large games can be estimated quite accurately through sampling and simulation.
format Preprint
id arxiv_https___arxiv_org_abs_2408_11146
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Swim till You Sink: Computing the Limit of a Game
Hakim, Rashida
Milionis, Jason
Papadimitriou, Christos
Piliouras, Georgios
Computer Science and Game Theory
Machine Learning
Theoretical Economics
During 2023, two interesting results were proven about the limit behavior of game dynamics: First, it was shown that there is a game for which no dynamics converges to the Nash equilibria. Second, it was shown that the sink equilibria of a game adequately capture the limit behavior of natural game dynamics. These two results have created a need and opportunity to articulate a principled computational theory of the meaning of the game that is based on game dynamics. Given any game in normal form, and any prior distribution of play, we study the problem of computing the asymptotic behavior of a class of natural dynamics called the noisy replicator dynamics as a limit distribution over the sink equilibria of the game. When the prior distribution has pure strategy support, we prove this distribution can be computed efficiently, in near-linear time to the size of the best-response graph. When the distribution can be sampled -- for example, if it is the uniform distribution over all mixed strategy profiles -- we show through experiments that the limit distribution of reasonably large games can be estimated quite accurately through sampling and simulation.
title Swim till You Sink: Computing the Limit of a Game
topic Computer Science and Game Theory
Machine Learning
Theoretical Economics
url https://arxiv.org/abs/2408.11146