Learning and Collusion in Multi-unit Auctions
Main Conference Track
Authors: Simina Branzei, Mahsa Derakhshan, Negin Golrezaei, Yanjun Han

In a carbon auction, licenses for CO2 emissions are allocated among multiple interested players. Inspired by this setting, we consider repeated multi-unit auctions with uniform pricing, which are widely used in practice. Our contribution is to analyze these auctions in both the offline and online settings, by designing efficient bidding algorithms with low regret and giving regret lower bounds. We also analyze the quality of the equilibria  in  two  main variants of the auction, finding that one  variant is susceptible to collusion among the bidders while the other is not.