{"type":"ScholarlyArticle","title":"Fair Equilibria in Sponsored Search Auctions: The Advertisers’ Perspective","authors":[{"name":"Georgios Birmpas","slug":"georgios-birmpas","given":"Georgios","family":"Birmpas","affiliation":"Department of Computer, Control and Management Engineering , Sapienza University , Rome , Italy"},{"name":"Andrea Celli","slug":"andrea-celli","given":"Andrea","family":"Celli","affiliation":"Department of Computing Sciences , Bocconi University , Milan , Italy"},{"name":"Riccardo Colini-Baldeschi","slug":"riccardo-colini-baldeschi","given":"Riccardo","family":"Colini-Baldeschi","affiliation":"Core Data Science , Meta , London , UK"},{"name":"Stefano Leonardi","slug":"stefano-leonardi","given":"Stefano","family":"Leonardi","affiliation":"Department of Computer, Control and Management Engineering , Sapienza University , Rome , Italy"}],"abstract":"In this work we introduce a new class of mechanisms composed of a traditional Generalized Second Price (GSP) auction, and a fair division scheme in order to achieve some desired level of fairness between groups of Bayesian strategic advertisers. We propose two mechanisms, beta-Fair GSP and GSP-EFX, that compose GSP with, respectively, an envy-free up to one item, and an envy-free up to any item fair division scheme. The payments of GSP are adjusted in order to compensate advertisers that suffer a loss of efficiency due the fair division stage. We investigate the strategic learning implications of the deployment of sponsored search auction mechanisms that obey to such fairness criteria. We prove that, for both mechanisms, if bidders play so as to minimize their external regret they are guaranteed to reach an equilibrium with good social welfare. We also prove that the mechanisms are budget balanced, so that the payments charged by the traditional GSP mechanism are a good proxy of the total compensation offered to the advertisers. Finally, we evaluate the quality of the allocations through experiments on real-world data.","doi":"10.24963/ijcai.2022/14","url":"https://ijcai.org/proceedings/2022/14","pdf":"https://ijcai.org/proceedings/2022/0014.pdf","markdown":"https://ijcai.org/proceedings/2022/14.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/14","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":14,"pages":{"first":95,"last":101},"keywords":["Agent-based and Multi-agent Systems: Mechanism Design","Agent-based and Multi-agent Systems: Algorithmic Game Theory"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986874","length_sec":58,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985017","length_sec":313,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Amanatidis et al., 2019] Georgios Amanatidis, Apostolos Ntokos, and Evangelos Markakis. 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