{"type":"ScholarlyArticle","title":"Mechanism Design with Predictions","authors":[{"name":"Chenyang Xu","slug":"chenyang-xu","given":"Chenyang","family":"Xu","affiliation":"College of Computer Science , Zhejiang University"},{"name":"Pinyan Lu","slug":"pinyan-lu","given":"Pinyan","family":"Lu","affiliation":"ITCS , Shanghai University of Finance and Economics; Huawei TCS Lab"}],"abstract":"Improving algorithms via predictions is a very active research topic in recent years. This paper initiates the systematic study of mechanism design in this model. In a number of well-studied mechanism design settings, we make use of imperfect predictions to design mechanisms that perform much better than traditional mechanisms if the predictions are accurate (consistency), while always retaining worst-case guarantees even with very imprecise predictions (robustness). Furthermore, we refer to the largest prediction error sufficient to give a good performance as the error tolerance of a mechanism, and observe that an intrinsic tradeoff among consistency, robustness and error tolerance is common for mechanism design with predictions.","doi":"10.24963/ijcai.2022/81","url":"https://ijcai.org/proceedings/2022/81","pdf":"https://ijcai.org/proceedings/2022/0081.pdf","markdown":"https://ijcai.org/proceedings/2022/81.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/81","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":81,"pages":{"first":571,"last":577},"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/38986694","length_sec":63,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984837","length_sec":327,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Anand et al., 2020] Keerti Anand, Rong Ge, and Debmalya Panigrahi. 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