Revenue Maximising Adaptive Auctioneer Agent

Authors:
Janine Claire Pike;Elizabeth Marie Ehlers
Affiliations:
Academy for Information Technology, University of Johannesburg, Johannesburg, South Africa;Academy for Information Technology, University of Johannesburg, Johannesburg, South Africa
Venue:
PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
Year:
2008

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Abstract

Auction theory has proven that auction revenue is influenced by factors such as the auction format and the auction parameters. The Revenue Maximising Adaptive Auctioneer (RMAA) agent model has been developed with the aim of generating maximum auction revenue by adapting the auction format and parameters to suit the auction environment. The RMAA agent uses a learning classifier system to learn which rules are profitable in a particular bidding environment. The profitable rules are then exploited by the RMAA agent to generate maximum revenue. The RMAA agent model can effectively adapt to a real time dynamic auction environment.