A Risk-Based Bidding Strategy for Continuous Double Auctions

We develop a novel bidding strategy that software agents can use to buy and sell goods in Continuous Double Auctions (CDAs). Our strategy involves the agent forming a bid or ask by assessing the degree of risk involved and making a prediction about the competitive equilibrium that is likely to be reached in the marketplace. We benchmark our strategy against two of the most common strategies for CDAs, namely the Zero-Intelligence and the ZeroIntelligence Plus strategies, and we show that our agents outperform these benchmarks. Specifically, our agents win in 100% of the simulations against the ZI agents and, on average, 75% of the games against the ZIP agents.

• Type: Conference
• Year: 2004
• Where: ECAI
• Authors: Perukrishnen Vytelingum, Rajdeep K. Dash, Esther David, Nicholas R. Jennings
• Keywords: Artificial Intelligence, Continuous Double Auctions, ECAI 2004, Software Agents, ZeroIntelligence Plus Strategies