A risk-based bidding strategy for continuous double auctions
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 Zero-Intelligence 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.
Vytelingum, P.
418675f3-cbda-47bc-8336-474fe328ac99
Dash, R.K.
688bf118-f42f-42bc-80f7-e915330f85d5
David, E.
50a83b47-a498-4536-8947-37a5f6cf7fba
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
2004
Vytelingum, P.
418675f3-cbda-47bc-8336-474fe328ac99
Dash, R.K.
688bf118-f42f-42bc-80f7-e915330f85d5
David, E.
50a83b47-a498-4536-8947-37a5f6cf7fba
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Vytelingum, P., Dash, R.K., David, E. and Jennings, N. R.
(2004)
A risk-based bidding strategy for continuous double auctions.
16th European Conference on Artificial Intelligence, 79-83, Valencia, Spain.
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Conference or Workshop Item
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Abstract
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 Zero-Intelligence 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.
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Published date: 2004
Additional Information:
Event Dates: 2004
Venue - Dates:
16th European Conference on Artificial Intelligence, 79-83, Valencia, Spain, 2004-01-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 259567
URI: http://eprints.soton.ac.uk/id/eprint/259567
PURE UUID: 65c4d734-0703-41eb-bba2-a6a6ae7bdf58
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Date deposited: 06 Sep 2004
Last modified: 14 Mar 2024 06:27
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Contributors
Author:
P. Vytelingum
Author:
R.K. Dash
Author:
E. David
Author:
N. R. Jennings
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