Congestion Games with Distance-Based Strict Uncertainty

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Congestion Games with Distance-Based Strict Uncertainty

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Title: Congestion Games with Distance-Based Strict Uncertainty
Author: Meir, Reshef; Parkes, David C.

Note: Order does not necessarily reflect citation order of authors.

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.
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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.
Published Version: https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/download/10058/9398
Other Sources: http://arxiv.org/pdf/1411.4943v1.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:17145150
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