Abstract
This paper is my undergratuate thesis focusing on strategies in Lowest Unique Bid Auctions (LUBA).
Lowest Unique Bid Auctions are a kind of games in which the agent with the lowest unique bid wins.
In this research, I studied the behaviors of agents in the LUBA game. First, I mathematically defined the
game and then proposed several models using different decision rules. I presented the models’ simulations
with comparison to recorded behaviors from real-life games. I analyzed the discrepancy between my models
and the data, and proposed potential solutions to this problem. Lastly, I discussed the potential applications
of my research in other games with similar structures and in the research at industrial organization.