The aim of this dissertation is to develop a suitable bidding strategy for an internet bidding agent that allows the agent to obtain the lowest possible price for a desired product at an internet auction. The bidding strategy is obtained under the constraint of limited information available about the strategies of the opponents. The agent will operate in an internet auction environment. Therefore classic auction theory is researched and explained. Auctions are widely used to bring buyers and sellers of products together and to create a market to buy and sell goods. The buyer wants to pay the lowest possible price and the seller wants to receive the highest possible price. However, the seller has no influence on the final selling price of the product. Instead the price is determined by the buyers. The agent will place bids on the auction site on behalf of the human instructor. The bidding agent will make use of the theory behind auctions to influence the other bidders on the auction to make the lowest possible bids. The model suggested in this dissertation, the regressive bidding agent model (RBA model), will incorporate auction theory to create a suitable agent. The agent will predict the future bids of opponents on the auction, basing its predictions on a regressive function. The agent will base its own bids placed at the auction on the bidding time remaining at the auction together with the bids placed by other bidders on the auction. / Prof. E.M. Ehlers
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:8613 |
| Date | 24 April 2008 |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
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