The Price of Anarchy in Auctions
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Abstract (arXiv)
This survey outlines a general and modular theory for proving approximation guarantees for equilibria of auctions in complex settings. This theory complements traditional economic techniques, which generally focus on exact and optimal solutions and are accordingly limited to relatively stylized settings. We highlight three user-friendly analytical tools: smoothness-type inequalities, which immediately yield approximation guarantees for many auction formats of interest in the special case of complete information and deterministic strategies; extension theorems, which extend such guarantees to randomized strategies, no-regret learning outcomes, and incomplete-information settings; and composition theorems, which extend such guarantees from simpler to more complex auctions. Combining these tools yields tight worst-case approximation guarantees for the equilibria of many widely-used auction formats.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jul 2016.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 2; 2025: 2.
11 papers.
- 2021Near-Optimal No-Regret Learning in General Gamescited by 85
- 2023How Bad is Top-K Recommendation under Competing Content Creators?cited by 27
- 2021Auctions Between Regret-Minimizing Agentscited by 22
- 2023Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamicscited by 20
- 2025Faster Rates for No-Regret Learning in General Games via Cautious Optimismcited by 10
- 2023Learning and Collusion in Multi-unit Auctionscited by 5
- 2025Expected Variational Inequalitiescited by 5
- 2023Learning in Repeated Multi-Unit Pay-As-Bid Auctionscited by 3
- 2024Games with Payments between Learning Agentscited by 3
- 2022An Algorithmic Introduction to Savings Circlescited by 0
- 2024Artificial Intelligence for Multi-Unit Auction designcited by 0
- 2025Faster Rates for No-Regret Learning in General Games via Cautious Optimism31 Mar 2025
- 2025Expected Variational Inequalities25 Feb 2025
- 2024Games with Payments between Learning Agents31 May 2024
- 2024Artificial Intelligence for Multi-Unit Auction design24 Apr 2024
- 2023Learning in Repeated Multi-Unit Pay-As-Bid Auctions27 Jul 2023
- 2023Learning and Collusion in Multi-unit Auctions27 May 2023
- 2023How Bad is Top-K Recommendation under Competing Content Creators?3 Feb 2023
- 2023Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics30 Jan 2023
- 2022An Algorithmic Introduction to Savings Circles23 Mar 2022
- 2021Auctions Between Regret-Minimizing Agents22 Oct 2021
- 2021Near-Optimal No-Regret Learning in General Games16 Aug 2021