{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:42:17Z","timestamp":1723016537205},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>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?\n\n\n\nWe show that P can obtain a \u0398(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 \u03b1, we obtain an \u03a9(log log \u03b1 \/ log \u03b1)-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\/\u03b1 cannot be avoided. If the utilities of P and A for each option are related by a factor \u03b2, we obtain an \u03a9(1 \/ log \u03b2)-approximation, and O(log log \u03b2 \/ log \u03b2) is best possible.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/281","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"2528-2536","source":"Crossref","is-referenced-by-count":0,"title":["Delegated Online Search"],"prefix":"10.24963","author":[{"given":"Pirmin","family":"Braun","sequence":"first","affiliation":[{"name":"Goethe University Frankfurt, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niklas","family":"Hahn","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, LIP6 UMR 7606, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Hoefer","sequence":"additional","affiliation":[{"name":"Goethe University Frankfurt, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Conrad","family":"Schecker","sequence":"additional","affiliation":[{"name":"Goethe University Frankfurt, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2023","name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","start":{"date-parts":[[2023,8,19]]},"theme":"Artificial Intelligence","location":"Macau, SAR China","end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:44:14Z","timestamp":1691743454000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/281"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/281","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}