Zeng, Mengya (2015-05). Reverse Auction Bidding - Artificially Intelligent Player's Interference with Other Bidders. Master's Thesis.
Reverse Auction Bidding is not a new procurement method in the construction industry. Unlike a traditional auction system, the Reverse Auction bidding system uses a bidding activities method completed anonymously using prequalified bidders during a certain auction time period or with a known end constraint. The basic premise for the auction is that the current best auction price can be seen through the whole auction process by both bidders and owner. The incentive is for noncompetitive bidders to lower the price. The study of Reverse Auction Bidding was first introduced to Texas A&M University in 2004, and continue with a series of study. This study is an ongoing study into the purchase of goods from a set of suppliers by a single purchaser. This research has progressed to new stage of introducting of an AI Player. A previous study proved that a human surrogate from the owner side could interfere with the free market. This research tried to find out a series of rules and regulations for the AI Player to drive down the profit to the owner's side. During the research, three human bidders and one AI Player participated in a new Reverse Auction game. The time intervals and bidding amounts of this new game were recorded, which provided the basic information to the research for her further analysis. The result showed that the AI Player was spotted by the bidders, and AI bidder was neutralized effectively from the game, where the other bidders returned to normal play. Further studies are still needed to explore the time rules for the AI Player.