Heuristic bidding strategies for multiple heterogeneous auctions
Heuristic bidding strategies for multiple heterogeneous auctions
This paper investigates utility maximising bidding heuristics for agents that participate in multiple heterogeneous auctions, in which the auction format and the starting and closing times can be different. Our strategy allows an agent to procure one or more items and to participate in any number of auctions. For this case, forming an optimal bidding strategy by global utility maximisation is computationally intractable, and so we develop two-stage heuristics that first provide reasonable bidding thresholds with simple strategies before deciding which auctions to participate in. The proposed approach leads to an average gain of at least 24% in agent utility over commonly used benchmarks.
300-304
Yuen, D.
14e9ad43-c8e2-439b-b28f-4f3a73d5705e
Byde, A.
4af131a0-6242-4a2c-a85d-a494edccc8ea
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
2006
Yuen, D.
14e9ad43-c8e2-439b-b28f-4f3a73d5705e
Byde, A.
4af131a0-6242-4a2c-a85d-a494edccc8ea
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Yuen, D., Byde, A. and Jennings, N. R.
(2006)
Heuristic bidding strategies for multiple heterogeneous auctions.
17th European Conference on Artificial Intelligence (ECAI-06), Riva del Garda, Italy.
28 Aug - 01 Sep 2006.
.
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Conference or Workshop Item
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Abstract
This paper investigates utility maximising bidding heuristics for agents that participate in multiple heterogeneous auctions, in which the auction format and the starting and closing times can be different. Our strategy allows an agent to procure one or more items and to participate in any number of auctions. For this case, forming an optimal bidding strategy by global utility maximisation is computationally intractable, and so we develop two-stage heuristics that first provide reasonable bidding thresholds with simple strategies before deciding which auctions to participate in. The proposed approach leads to an average gain of at least 24% in agent utility over commonly used benchmarks.
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ecai06-yuen.pdf
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Published date: 2006
Venue - Dates:
17th European Conference on Artificial Intelligence (ECAI-06), Riva del Garda, Italy, 2006-08-28 - 2006-09-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 262600
URI: http://eprints.soton.ac.uk/id/eprint/262600
PURE UUID: 6719d23d-c634-4c8c-be90-23bbeda0c025
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Date deposited: 16 May 2006
Last modified: 14 Mar 2024 07:14
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Contributors
Author:
D. Yuen
Author:
A. Byde
Author:
N. R. Jennings
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