We study a general class of repeated auctions, such as the ones found in electricity markets,
as multi-agent games between the bidders. In such a repeated setting, bidders can adapt
their strategies online using no-regret algorithms based on the data observed in the
previous auction rounds. Well-studied no-regret algorithms depend on the feedback
information available at every round, and can be mainly distinguished as bandit (or payoff-
based), and full-information. However, the information structure found in auctions lies in …