{"type":"ScholarlyArticle","title":"Delegated Online Search","authors":[{"name":"Pirmin Braun","slug":"pirmin-braun","given":"Pirmin","family":"Braun","affiliation":"Goethe University Frankfurt , Germany"},{"name":"Niklas Hahn","slug":"niklas-hahn","given":"Niklas","family":"Hahn","affiliation":"Sorbonne Université , CNRS , LIP6 UMR 7606 , Paris , France"},{"name":"Martin Hoefer","slug":"martin-hoefer","given":"Martin","family":"Hoefer","affiliation":"Goethe University Frankfurt , Germany"},{"name":"Conrad Schecker","slug":"conrad-schecker","given":"Conrad","family":"Schecker","affiliation":"Goethe University Frankfurt , Germany"}],"abstract":"In a delegation problem, a principal P with commitment power tries to pick one out of n options. Each option is drawn independently from a known distribution. Instead of inspecting the options herself, P delegates the information acquisition to a rational and self-interested agent A. After inspection, A proposes one of the options, and P can accept or reject. In this paper, we study a natural online variant of delegation, in which the agent searches through the options in an online fashion. How can we design algorithms for P that approximate the utility of her best option in hindsight?\r\n\r\nWe show that P can obtain a Θ(1/n)-approximation and provide more fine-grained bounds independent of n based on two parameters. If the ratio of maximum and minimum utility for A is bounded by a factor α, we obtain an Ω(log log α / log α)-approximation algorithm and show that this is best possible. If P cannot distinguish options with the same value for herself, we show that ratios polynomial in 1/α cannot be avoided. If the utilities of P and A for each option are related by a factor β, we obtain an Ω(1 / log β)-approximation, and O(log log β / log β) is best possible.","doi":"10.24963/ijcai.2023/281","url":"https://ijcai.org/proceedings/2023/281","pdf":"https://ijcai.org/proceedings/2023/0281.pdf","markdown":"https://ijcai.org/proceedings/2023/281.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/281","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Game Theory and Economic Paradigms","track":"Main Track","number":281,"pages":{"first":2528,"last":2536},"keywords":["Game Theory and Economic Paradigms: GTEP: Auctions and market-based systems","Agent-based and Multi-agent Systems: MAS: Agent communication","Game Theory and Economic Paradigms: GTEP: Mechanism design"],"videos":[],"references":[{"position":1,"raw":"[Alonso and Matouschek, 2008] Ricardo Alonso and Niko Matouschek. 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