Designing the Market Game for a Trading Agent Competition
IEEE Internet Computing
Walverine: a Walrasian trading agent
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
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
Bidding under uncertainty: theory and experiments
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Decision-theoretic bidding based on learned density models in simultaneous, interacting auctions
Journal of Artificial Intelligence Research
Designing a successful trading agent: A fuzzy set approach
IEEE Transactions on Fuzzy Systems
Comparative analysis of multi-agents competing for trading agents competition
AIC'08 Proceedings of the 8th conference on Applied informatics and communications
RoxyBot-06: stochastic prediction and optimization in TAC travel
Journal of Artificial Intelligence Research
Strategic software agents in continuous double auction under dynamic environments
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
A computing approach to agent bidding in continuous double auction
Web Intelligence and Agent Systems
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This paper presents a new bidding strategy for continuous double auctions (CDA) designed for Mertacor, a successful trading agent, which won the first price in the “travel game” of Trading Agent Competition (TAC) for 2005. TAC provides a realistic benchmarking environment in which various travel commodities are offered in simultaneous online auctions. Among these, entertainment tickets are traded in CDA. The latter, represent the most dynamic part of the TAC game, in which agents are both sellers and buyers. In a CDA many uncertainty factors are introduced, because prices are constantly changing during the game and price fluctuations are hard to be predicted. In order to deal with these factors of uncertainty we have designed a strategy based on achieving a pre-defined long-term profit. This preserves the bidding attitude of our agent and shows flexibility in changes of the environment. We finally present and discuss the results of TAC-05, as well as an analysis of agents performance in the entertainment auctions.