SIAM Journal on Computing· 2026Q1
The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations
- 0citations
- Q1SCImago
- 2026year
Short summary
A new characterization shows that increasing auction transparency (information on competitor bids) significantly reduces a bidder's minimax regret in first-price auctions, especially in environments with adversarial valuations.
AI-generated from the title and abstract; the full text is not read.
Key points
- Minimizes regret for a single bidder in repeated first-price auctions with unknown item values.
- Introduces a characterization of minimax regret based on auction transparency (information on competitor bids).
- Results are robust across stochastic, adversarial, and smoothed adversarial environments.
- Transparency's impact on learning speed and optimal bidding strategies is quantified.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract. We study the problem of regret minimization for a single bidder in a sequence of first-price auctions where the bidder discovers the item’s value only if the auction is won. Our main contribution is a complete characterization, up to logarithmic factors, of the minimax regret in terms of the auction’s transparency, which controls the amount of information on competing bids disclosed by the auctioneer at the end of each auction. Our results hold under different assumptions (stochastic, adversarial, and their smoothed variants) on the environment generating the bidder’s valuations and competing bids. These minimax rates reveal how the interplay between transparency and the nature of the environment affects how fast one can learn to bid optimally in first-price auctions.
The authors' abstract, as published at the source. SIAM Journal on Computing, 2026 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Management Science and Operations Research
Management Science and Operations ResearchDecision Sciences