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Authors: Yida Xu and Hamidou Tembine

Affiliation: New York University, United Arab Emirates

ISBN: 978-989-758-275-2

Keyword(s): LUBA, Auction, Game Theory, Imitative Learning, Reinforcement Learning.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Distributed and Mobile Software Systems ; Economic Agent Models ; Enterprise Information Systems ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Machine Learning ; Multi-Agent Systems ; Soft Computing ; Software Engineering ; Symbolic Systems

Abstract: The recent online platforms propose multiple items for bidding. The state of the art, however, is limited to the analysis of one item auction. In this paper we study multi-item lowest unique bid auctions (LUBA) in discrete bid spaces under budget constraints. We show the existence of mixed Bayes-Nash equilibria for an arbitrary number of bidders and items. The equilibrium is explicitly computed in two bidder setup with resubmission possibilities. In the general setting we propose a distributed strategic learning algorithm to approximate equilibria. Computer simulations indicate that the error quickly decays in few number of steps by means of speedup techniques. When the number of bidders per item follows a Poisson distribution, it is shown that the seller can get a non-negligible revenue on several items, and hence making a partial revelation of the true value of the items.

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Paper citation in several formats:
Xu, Y. and Tembine, H. (2018). Lowest Unique Bid Auctions with Resubmission Opportunities.In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-275-2, pages 330-337. DOI: 10.5220/0006548203300337

@conference{icaart18,
author={Yida Xu. and Hamidou Tembine.},
title={Lowest Unique Bid Auctions with Resubmission Opportunities},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2018},
pages={330-337},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006548203300337},
isbn={978-989-758-275-2},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Lowest Unique Bid Auctions with Resubmission Opportunities
SN - 978-989-758-275-2
AU - Xu, Y.
AU - Tembine, H.
PY - 2018
SP - 330
EP - 337
DO - 10.5220/0006548203300337

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