{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T21:58:04Z","timestamp":1757541484757},"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":[[2020,7]]},"abstract":"<jats:p>The problem of multi-armed bandit (MAB) with fairness constraint has emerged as an important research topic recently. For such problems, one common objective is to maximize the total rewards within a fixed round of pulls, while satisfying the fairness requirement of a minimum selection fraction for each individual arm in the long run. Previous works have made substantial advancements in designing efficient online selection solutions, however, they fail to achieve a sublinear regret bound when incorporating such fairness constraints. In this paper, we study a combinatorial MAB problem with concave objective and fairness constraints. In particular, we adopt a new approach that combines online convex optimization with bandit methods to design selection algorithms. Our algorithm is computationally efficient, and more importantly, manages to achieve a sublinear regret bound with probability guarantees. Finally, we evaluate the performance of our algorithm via extensive simulations and demonstrate that it outperforms the baselines substantially.<\/jats:p>","DOI":"10.24963\/ijcai.2020\/354","type":"proceedings-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T12:12:10Z","timestamp":1594210330000},"page":"2554-2560","source":"Crossref","is-referenced-by-count":7,"title":["Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints"],"prefix":"10.24963","author":[{"given":"Huanle","family":"Xu","sequence":"first","affiliation":[{"name":"Dongguan University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wing Cheong","family":"Lau","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Li","sequence":"additional","affiliation":[{"name":"Dongguan University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-PRICAI-2020","name":"Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}","start":{"date-parts":[[2020,7,11]]},"theme":"Artificial Intelligence","location":"Yokohama, Japan","end":{"date-parts":[[2020,7,17]]}},"container-title":["Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T02:14:38Z","timestamp":1594260878000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2020\/354"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2020\/354","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}