In a course bidding system, there are more students than the number of available seats for course. To enroll course, have to bid using their tokens and system will fill up with top bidders. Since limit tokens, they allocate wisely. this paper, we apply genetic algorithm search best way such that it maximizes probability successful enrollment. estimate probability, train logistic regression on r...

ITERATIVE COMBINATORIAL AUCTIONS: ACHIEVING ECONOMIC AND COMPUTATIONAL EFFICIENCY David Christopher Parkes Supervisor: Lyle H. Ungar This thesis presents new auction-based mechanisms to coordinate systems of selfinterested and autonomous agents, and new methods to design such mechanisms and prove their optimality. Computation is increasingly carried out on open networks, with self-interested pr...

T seller’s threshold price in name-your-own-price auctions varies over time. However, consumers must bid without knowing when these variations occur because the threshold price is unobservable to them. This paper uses an analytical model and laboratory auctions to explore how the frequency of changes in the threshold price impacts consumer bidding behavior in name-your-own-price auctions. In pa...

We consider a general class of Bayesian Games where each players utility depends on his type (possibly multidimensional) and on the strategy profile and where players’ types are distributed independently. We show that if their full information version for any fixed instance of the type profile is a smooth game then the Price of Anarchy bound implied by the smoothness property, carries over to t...

Internet auctions have resulted in much data that may shed light on buying and selling behavior. Furthermore, they have allowed for field experiments to explore these phenomena with more control and with greater depth. Finally, they have revealed new behavioral patterns worthy of exploration. One of these behaviors is late bidding, or sniping, which occurs when people place bids close to the au...

This paper develops a strategy for identifying and estimating the valuation distribution in ascending auctions where bidders have an unknown number of bidding opportunities. Our model leads to equilibrium jump bidding and potentially inefficient allocations. Our identification approach requires few assumptions on the types of equilibria played. In particular, we need not assume that a unique eq...