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.
@article{arxiv.1411.4943,
title = {Congestion Games with Distance-Based Strict Uncertainty},
author = {Reshef Meir and David Parkes},
journal= {arXiv preprint arXiv:1411.4943},
year = {2017}
}
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The full version of a paper from AAAI'15 (to appear)