A principled study of the design tradeoffs for autonomous trading agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Characterizing effective auction mechanisms: insights from the 2007 TAC market design competition
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
IEEE Transactions on Evolutionary Computation
Experimental Market Mechanism Design for Double Auction
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
What the 2007 TAC Market Design Game tells us about effective auction mechanisms
Autonomous Agents and Multi-Agent Systems
EA2: The Winning Strategy for the Inaugural Lemonade Stand Game Tournament
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Competition between markets and the CAT Tournament: Guest editors' introduction to the special issue
Electronic Commerce Research and Applications
AstonCAT-plus: an efficient specialist for the TAC market design tournament
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Autonomous Agents and Multi-Agent Systems
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In this paper we describe the IAMwildCAT agent, designed for the TAC Market Design game which is part of the International Trading Agent Competition. The objective of an agent in this competition is to effectively manage and operate a market that attracts traders to compete for resources in it. This market, in turn, competes against markets operated by other competition entrants and the aim is to maximise the market and profit share of the agent, as well as its transaction success rate. To do this, the agent needs to continually monitor and adapt, in response to the competing marketplaces, the rules it uses to accept offers, clear the market, price the transactions and charge the traders. Given this context, this paper details IAMwildCAT's strategic behaviour and describes the wide techniques we developed to operationalise this. Finally, we empirically analyse our agent in different environments, including the 2007 competition where it ranked first.