Distributed representations of bids in lowest unique bid auctions

Yida Xu, Tembine Hamidou

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, we study multi-item lowest unique bid auctions (LUBA) with resubmission under budget constraints. A representation of bids that can perceive the rich strategic meaning in the world of multi-item LUBA with resubmission is learned by an efficient method-Skip-gram model. We created and maintained a dataset which contains the relevant information of LUBA, including the winning bid combination, budget constraints, and the number of participated bidders. An Android-based application is developed and contributes the construction of the dataset. The quantitative analysis displays that the representation cluster can reflect similarities in terms of numerical information, cultural and aesthetic preference, and other bidder's behaviors. The learned representation can serve as a guide for bidders who seek to maximize their payoff and feed into a sequence generation model, such as recurrent neural network, to produce the bids combination.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3173-3178
    Number of pages6
    ISBN (Electronic)9781538612439
    DOIs
    StatePublished - Jul 6 2018
    Event30th Chinese Control and Decision Conference, CCDC 2018 - Shenyang, China
    Duration: Jun 9 2018Jun 11 2018

    Other

    Other30th Chinese Control and Decision Conference, CCDC 2018
    CountryChina
    CityShenyang
    Period6/9/186/11/18

    Fingerprint

    Auctions
    Lowest
    Budget Constraint
    Recurrent neural networks
    Recurrent Neural Networks
    Quantitative Analysis
    Maximise
    Chemical analysis
    Model
    Bid

    Keywords

    • auction
    • embedding space
    • game theory
    • LUBA

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Control and Optimization
    • Decision Sciences (miscellaneous)

    Cite this

    Xu, Y., & Hamidou, T. (2018). Distributed representations of bids in lowest unique bid auctions. In Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018 (pp. 3173-3178). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC.2018.8407670

    Distributed representations of bids in lowest unique bid auctions. / Xu, Yida; Hamidou, Tembine.

    Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3173-3178.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Xu, Y & Hamidou, T 2018, Distributed representations of bids in lowest unique bid auctions. in Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc., pp. 3173-3178, 30th Chinese Control and Decision Conference, CCDC 2018, Shenyang, China, 6/9/18. https://doi.org/10.1109/CCDC.2018.8407670
    Xu Y, Hamidou T. Distributed representations of bids in lowest unique bid auctions. In Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3173-3178 https://doi.org/10.1109/CCDC.2018.8407670
    Xu, Yida ; Hamidou, Tembine. / Distributed representations of bids in lowest unique bid auctions. Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3173-3178
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