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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mochon, A. Quintana, D. Yago Saez Isasi, P. |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Appl. Econ., UNED, Madrid, Spain (Mochon, A.) |
| Abstract | The increasing use of auctions has led to a growing interest in the subject. A recent method used for carrying out examinations on auctions has been the design of computational simulations. The aim of this paper is to develop a genetic algorithm to find bidders' optimal strategies for a specific dynamic multi-unit auction. The algorithm provides the bidding strategy (defined as the action to be taken under different auction conditions) that maximizes the bidder's payoff. The algorithm is tested under several experimental environments, number of bidders and quantity of lots auctioned. The results suggest that the approach leads to strategies that outperform canonical strategies. |
| Starting Page | 2645 |
| Ending Page | 2652 |
| File Size | 1610700 |
| Page Count | 8 |
| File Format | |
| ISBN | 0780393635 |
| DOI | 10.1109/CEC.2005.1555026 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-09-02 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Evolutionary computation Environmental economics Artificial intelligence Genetic algorithms Learning systems Computational modeling Testing Internet Government Art |
| Content Type | Text |
| Resource Type | Article |
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