{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T11:28:13Z","timestamp":1776252493739,"version":"3.50.1"},"reference-count":50,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T00:00:00Z","timestamp":1722384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Recomm. Syst."],"published-print":{"date-parts":[[2024,12,31]]},"abstract":"<jats:p>\n            Online platforms in the Internet Economy commonly incorporate recommender systems that recommend products (or \u201carms\u201d) to users (or \u201cagents\u201d). A key challenge in this domain arises from myopic agents who are naturally incentivized to\n            <jats:italic>exploit<\/jats:italic>\n            by choosing the optimal arm based on current information, rather than\n            <jats:italic>exploring<\/jats:italic>\n            various alternatives to gather information that benefits the collective. We propose a new recommender system that aligns with agents\u2019 incentives while achieving asymptotically optimal performance, as measured by regret in repeated interactions. Our framework models this incentive-aware system as a multi-agent bandit problem in two-sided markets, where the interactions of agents and arms are facilitated by recommender systems on online platforms. This model incorporates incentive constraints induced by agents\u2019 opportunity costs. In scenarios where opportunity costs are known to the platform, we show the existence of an incentive-compatible recommendation algorithm. This algorithm pools recommendations between a genuinely good arm and an unknown arm using a randomized and adaptive strategy. Moreover, when these opportunity costs are unknown, we introduce an algorithm that randomly pools recommendations across all arms, utilizing the cumulative loss from each arm as feedback for strategic exploration. We demonstrate that both algorithms satisfy an ex-post fairness criterion, which protects agents from over-exploitation. All code for using the proposed algorithms and reproducing results is made available on GitHub.\n          <\/jats:p>","DOI":"10.1145\/3674158","type":"journal-article","created":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T11:17:04Z","timestamp":1718968624000},"page":"1-38","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Incentive-Aware Recommender Systems in Two-Sided Markets"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5889-5201","authenticated-orcid":false,"given":"Xiaowu","family":"Dai","sequence":"first","affiliation":[{"name":"University of California, Los Angeles, Los Angeles, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7869-2328","authenticated-orcid":false,"given":"Wenlu","family":"Xu","sequence":"additional","affiliation":[{"name":"University of California, Los Angeles, Los Angeles, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8981-0154","authenticated-orcid":false,"given":"Yuan","family":"Qi","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China and Ant Group, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8935-817X","authenticated-orcid":false,"given":"Michael","family":"Jordan","sequence":"additional","affiliation":[{"name":"UC Berkeley, Berkeley, United States and Ant Group, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.3982\/ECTA15847"},{"key":"e_1_3_3_3_2","volume-title":"Repeated Games with Incomplete Information","author":"Aumann Robert J.","year":"1995","unstructured":"Robert J. 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