Project 1: Building a Second-Price Auction (Modeling and Strategy)
You has been hired by a major retailer to develop algorithms for an online ad auction. Your client knows a little about the multi-armed bandit literature and recognizes that it can spend money to explore, learning how likely users are to click on ads, or to exploit, spending on the most
promising users to maximize immediate payoffs. At the same time, there are other companies participating in the auction that may outbid your client, potentially interfering with these goals.
Your task is to model the ad auction and develop an effective algorithm for bidding in a landscape of strategic competitors. Your client plans to test your bidding algorithm against other bidding algorithms contributed by other data scientists, in order to select the most promising algorithm.
The Auction Rules
The is a game, involving a set of Bidder s on one side, and a set of User s on the other.
Each round represents an event in which a navigates to a website with a space for an ad.
When this happens, the Bidder s will place bids, and the winner gets to show their ad to the
User . The may click on the ad, or not click, and the winning
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