Congestion Games with Distance-Based Strict Uncertainty
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.
Cite
Text
Meir and Parkes. "Congestion Games with Distance-Based Strict Uncertainty." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9291Markdown
[Meir and Parkes. "Congestion Games with Distance-Based Strict Uncertainty." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/meir2015aaai-congestion/) doi:10.1609/AAAI.V29I1.9291BibTeX
@inproceedings{meir2015aaai-congestion,
title = {{Congestion Games with Distance-Based Strict Uncertainty}},
author = {Meir, Reshef and Parkes, David C.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2015},
pages = {986-992},
doi = {10.1609/AAAI.V29I1.9291},
url = {https://mlanthology.org/aaai/2015/meir2015aaai-congestion/}
}