@techreport{7d58dc619a2c4666b269e3c877cf29c9,
title = "How and Why to Manipulate Your Own Agent.",
abstract = "We consider strategic settings where several users engage in a repeated online interaction, assisted by regret-minimizing learning agents that repeatedly play a {"}game{"} on their behalf. We study the dynamics and average outcomes of the repeated game of the agents, and propose to view it as inducing a {"}meta-game{"} between the users. Our main focus is on whether users can benefit in this meta-game from {"}manipulating{"} their own agents by misreporting their parameters to them. We formally define the model of these meta-games between the users for general games and analyze the equilibria induced on the users in two classes of games in which the time-average of all regret-minimizing dynamics converge to a single equilibrium. ",
author = "Yoav Kolumbus and Noam Nisan",
year = "2021",
doi = "10.48550/arXiv.2112.07640",
language = "American English",
volume = "abs/2112.07640",
series = "CoRR",
type = "WorkingPaper",
}