Publication:
Congestion Games with Distance-Based Strict Uncertainty

Thumbnail Image

Date

2015

Published Version

Journal Title

Journal ISSN

Volume Title

Publisher

Association for the Advancement of Artificial Intelligence
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Meir, Reshef and David C. Parkes. 2015. Congestion Games with Distance-Based Strict Uncertainty. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, Austin, TX.

Research Data

Abstract

We put forward a new model of congestion games where agents have uncertainty over the routes used by other agents. We take a non-probabilistic approach, assuming that each agent knows that the number of agents using an edge is within a certain range. Given this uncertainty, we model agents who either minimize their worst-case cost (WCC) or their worst-case regret (WCR), and study implications on equilibrium existence, convergence through adaptive play, and efficiency. Under the WCC behavior the game reduces to a modified congestion game, and welfare improves when agents have moderate uncertainty. Under WCR behavior the game is not, in general, a congestion game, but we show convergence and efficiency bounds for a simple class of games.

Description

Keywords

Terms of Use

This article is made available under the terms and conditions applicable to Open Access Policy Articles (OAP), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories