Aggregating strategy for online auctions

Shigeaki Harada, Eiji Takimoto, Akira Maruoka

研究成果: 著書/レポートタイプへの貢献会議での発言

抜粋

We consider the online auction problem in which an auctioneer is selling an identical item each time when a new bidder arrives. It is known that results from online prediction can be applied and achieve a constant competitive ratio with respect to the best fixed price profit. These algorithms work on a predetermined set of price levels. We take into account the property that the rewards for the price levels are not independent and cast the problem as a more refined model of online prediction. We then use Vovk's Aggregating Strategy to derive a new algorithm. We give a general form of competitive ratio in terms of the price levels. The optimality of the Aggregating Strategy gives an evidence that our algorithm performs at least as well as the previously proposed ones.

元の言語英語
ホスト出版物のタイトルComputing and Combinatorics - 12th Annual International Conference, COCOON 2006, Proceedings
出版者Springer Verlag
ページ33-41
ページ数9
ISBN(印刷物)3540369252, 9783540369257
DOI
出版物ステータス出版済み - 1 1 2006
イベント12th Annual International Conference on Computing and Combinatorics, COCOON 2006 - Taipei, 台湾省、中華民国
継続期間: 8 15 20068 18 2006

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4112 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

その他

その他12th Annual International Conference on Computing and Combinatorics, COCOON 2006
台湾省、中華民国
Taipei
期間8/15/068/18/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Harada, S., Takimoto, E., & Maruoka, A. (2006). Aggregating strategy for online auctions. : Computing and Combinatorics - 12th Annual International Conference, COCOON 2006, Proceedings (pp. 33-41). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 4112 LNCS). Springer Verlag. https://doi.org/10.1007/11809678_6