11:00-12:00 Monday, 5 May 2025 Auditorium, Rectorate
Abstract
We present an auction model in which multiple autonomous bidders attempt to sell their goods with the goal of maximizing their profits. Bidders operate without knowledge of one another and adjust their bids solely based on their most recent performance behavior (myopic adaptation). More precisely, a bidder who is awarded in a given round will increase their selling price in the next round, while one who is not awarded will decrease it. In each round, the auctioneer purchases the lowest p-fraction of the total energy offered by the bidders. We find a system of diļ¬erential equations governing the macroscopic dynamics and derive it as a scaling limit of the microscopic model. We find an explicit solution for the max-price evolution and show that in the long run bidders coordinate, i.e. they tend to bid the same value only depending on their initial distribution and the value p. A phase transition appears when p = 1/2. Funded by Next Generation EU. Joint work with P. Ferrari, C. Franceschini, N. Manelli.