The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Optimal Auction Design
Open accessAbstract
This paper considers the problem faced by a seller who has a single object to sell to one of several possible buyers, when the seller has imperfect information about how much the buyers might be willing to pay for the object. The seller's problem is to design an auction game which has a Nash equilibrium giving him the highest possible expected utility. Optimal auctions are derived in this paper for a wide class of auction design problems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
COUNTERSPECULATION, AUCTIONS, AND COMPETITIVE SEALED TENDERS
Vickrey, W. (1961) · The Journal of Finance · doi:10.1111/j.1540-6261.1961.tb02789.x · Cited by 7,722
Cited by
The interdisciplinary study of coordination
Malone, T. W., & Crowston, K. (1994) · ACM Computing Surveys · doi:10.1145/174666.174668 · Cited by 3,504
Multiagent systems: algorithmic, game-theoretic, and logical foundations
(2009) · Choice Reviews Online · doi:10.5860/choice.46-5662 · Cited by 1,756
Luong, N. C., Xiong, Z., Wang, P., & Niyato, D. (2018) · 2018 IEEE International Conference on Communications (ICC) · doi:10.1109/icc.2018.8422743 · Cited by 229
Online Display Advertising Markets: A Literature Review and Future Directions
Choi, H., Mela, C. F., Balseiro, S. R., & Leary, A. (2020) · Information Systems Research · doi:10.1287/isre.2019.0902 · Cited by 181
The AI economist: taxation policy design via two-level deep multiagent reinforcement learning
Zheng, S., Trott, A., Srinivasa, S., Parkes, D. C., & Socher, R. (2022) · Science Advances · doi:10.1126/sciadv.abk2607 · Cited by 105
Private provision of discrete public goods with incomplete information
Menezes, F. M., Monteiro, P. K., & Temimi, A. (2001) · Journal of Mathematical Economics · doi:10.1016/s0304-4068(01)00059-3 · Cited by 76
Sustainable Growth and Token Economy Design: The Case of Steemit
Kim, M. S., & Chung, J. Y. (2018) · Sustainability · doi:10.3390/su11010167 · Cited by 74
Revenue Optimization with Approximate Bid Predictions
Medina, A. M., & Vassilvitskii, S. (2017) · arXiv · doi:10.48550/arxiv.1706.04732 · Cited by 51
Formal contracts mitigate social dilemmas in multi-agent reinforcement learning
Haupt, A., Christoffersen, P., Damani, M., & Hadfield-Menell, D. (2024) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-024-09682-5 · Cited by 5
“The setting of an agent proposing state-dependent reward transfers has received considerable attention in contract economics, compare the literature following [27], and mechanism design, compare [16, 28, 40].”
Social Status and Badge Design
Immorlica, N., Stoddard, G., & Syrgkanis, V. (2013) · arXiv · doi:10.48550/arxiv.1312.2299 · Cited by 5
Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
de Witt, C. S., Krawiecka, K., Krawczuk, I., Hagag, B., Anderson, W. L., Belcak, P., Bucknall, B., Cai, X., Chopra, A., Cohen, D., et al. (2025) · arXiv · doi:10.48550/arxiv.2505.02077 · Cited by 108
“…have studied security game equilibria (Conitzer & Sandholm, 2006), mechanism designers have studied incentive alignment in static settings (Myerson, 1981), and multi-agent learning researchers have studied the end-to-end learning dynamics of neural network policies (Busoniu et al., 2008;…”
Metadata
- Authors
- Myerson, R. B.
- Venue
- Mathematics of Operations Research
- Published
- 1981-02
- Volume
- 6
- Issue
- 1
- Pages
- 58-73
- ISSN
- 0364-765X (ISSN-L)
- 1526-5471
- OpenAlex
- W2029050771
- Cited by
- 5,920
- References
- 1
- FWCI
- 13.18
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
