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Computer Science > Computer Science and Game Theory
Title: Artificial Intelligence for Multi-Unit Auction design
(Submitted on 24 Apr 2024 (v1), last revised 29 Apr 2024 (this version, v2))
Abstract: Understanding bidding behavior in multi-unit auctions remains an ongoing challenge for researchers. Despite their widespread use, theoretical insights into the bidding behavior, revenue ranking, and efficiency of commonly used multi-unit auctions are limited. This paper utilizes artificial intelligence, specifically reinforcement learning, as a model free learning approach to simulate bidding in three prominent multi-unit auctions employed in practice. We introduce six algorithms that are suitable for learning and bidding in multi-unit auctions and compare them using an illustrative example. This paper underscores the significance of using artificial intelligence in auction design, particularly in enhancing the design of multi-unit auctions.
Submission history
From: Peyman Khezr [view email][v1] Wed, 24 Apr 2024 03:51:26 GMT (955kb,D)
[v2] Mon, 29 Apr 2024 05:07:18 GMT (1086kb,D)
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