Deep False-Name-Proof Auction Mechanisms

Yuko Sakurai, Satoshi Oyama, Mingyu Guo, Makoto Yokoo

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

We explore an approach to designing false-name-proof auction mechanisms using deep learning. While multi-agent systems researchers have recently proposed data-driven approaches to automatically designing auction mechanisms through deep learning, false-name-proofness, which generalizes strategy-proofness by assuming that a bidder can submit multiple bids under fictitious identifiers, has not been taken into account as a property that a mechanism has to satisfy. We extend the RegretNet neural network architecture to incorporate false-name-proof constraints and then conduct experiments demonstrating that the generated mechanisms satisfy false-name-proofness.

本文言語英語
ホスト出版物のタイトルPRIMA 2019
ホスト出版物のサブタイトルPrinciples and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings
編集者Matteo Baldoni, Mehdi Dastani, Beishui Liao, Yuko Sakurai, Rym Zalila Wenkstern
出版社Springer
ページ594-601
ページ数8
ISBN(印刷版)9783030337919
DOI
出版ステータス出版済み - 2019
イベント22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 - Turin, イタリア
継続期間: 10 28 201910 31 2019

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)
11873 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019
Countryイタリア
CityTurin
Period10/28/1910/31/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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