{"type":"ScholarlyArticle","title":"Optimal Anonymous Independent Reward Scheme Design","authors":[{"name":"Mengjing Chen","slug":"mengjing-chen","given":"Mengjing","family":"Chen","affiliation":"Tsinghua University"},{"name":"Pingzhong Tang","slug":"pingzhong-tang","given":"Pingzhong","family":"Tang","affiliation":"Tsinghua University"},{"name":"Zihe Wang","slug":"zihe-wang","given":"Zihe","family":"Wang","affiliation":"Renmin University of China; Beijing Key Laboratory of Big Data Management and Analysis Methods"},{"name":"Shenke Xiao","slug":"shenke-xiao","given":"Shenke","family":"Xiao","affiliation":"Tsinghua University"},{"name":"Xiwang Yang","slug":"xiwang-yang","given":"Xiwang","family":"Yang","affiliation":""}],"abstract":"We consider designing reward schemes that incentivize agents to create high-quality content (e.g., videos, images, text, ideas). The problem is at the center of a real-world application where the goal is to optimize the overall quality of generated content on user-generated content platforms. We focus on anonymous independent reward schemes (AIRS) that only take the quality of an agent's content as input. We prove the general problem is NP-hard. If the cost function is convex, we show the optimal AIRS can be formulated as a convex optimization problem and propose an efficient algorithm to solve it. Next, we explore the optimal linear reward scheme and prove it has a 1/2-approximation ratio, and the ratio is tight. Lastly, we show the proportional scheme can be arbitrarily bad compared to AIRS.","doi":"10.24963/ijcai.2022/24","url":"https://ijcai.org/proceedings/2022/24","pdf":"https://ijcai.org/proceedings/2022/0024.pdf","markdown":"https://ijcai.org/proceedings/2022/24.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/24","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":24,"pages":{"first":165,"last":171},"keywords":["Agent-based and Multi-agent Systems: Algorithmic Game Theory"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986796","length_sec":77,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984939","length_sec":294,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Alon et al., 2020] Tal Alon, Magdalen Dobson, Ariel D Procaccia, Inbal Talgam-Cohen, and Jamie Tucker-Foltz. 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