{"type":"ScholarlyArticle","title":"Incentive-Compatible Diffusion Auctions","authors":[{"name":"Bin Li","slug":"bin-li","given":"Bin","family":"Li","affiliation":"School of Computer Science & Engineering , University of Electronic Science and Technology of China"},{"name":"Dong Hao","slug":"dong-hao","given":"Dong","family":"Hao","affiliation":"School of Computer Science & Engineering , University of Electronic Science and Technology of China"},{"name":"Dengji Zhao","slug":"dengji-zhao","given":"Dengji","family":"Zhao","affiliation":"Shanghai Engineering Research Center of Intelligent Vision and Imaging , ShanghaiTech University"}],"abstract":"Diffusion auction is a new model in auction design. It can incentivize the buyers who have already joined in the auction to further diffuse the sale information to others via social relations, whereby both the seller's revenue and the social welfare can be improved. Diffusion auctions are essentially non-typical multidimensional mechanism design problems and agents' social relations are complicatedly involved with their bids. In such auctions, incentive-compatibility (IC) means it is best for every agent to honestly report her valuation and fully diffuse the sale information to all her neighbors. Existing work identified some specific mechanisms for diffusion auctions, while a general theory characterizing all incentive-compatible diffusion auctions is still missing. In this work, we identify a sufficient and necessary condition for all dominant-strategy incentive-compatible (DSIC) diffusion auctions. We formulate the monotonic allocation policies in such multidimensional problems and show that any monotonic allocation policy can be implemented in a DSIC diffusion auction mechanism. Moreover, given any monotonic allocation policy, we obtain the optimal payment policy to maximize the seller's revenue.","doi":"10.24963/ijcai.2020/33","url":"https://ijcai.org/proceedings/2020/33","pdf":"https://ijcai.org/proceedings/2020/0033.pdf","markdown":"https://ijcai.org/proceedings/2020/33.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/33","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Agent-based and Multi-agent Systems","track":"Main track","number":33,"pages":{"first":231,"last":237},"keywords":["Agent-based and Multi-agent Systems: Algorithmic Game Theory","Agent-based and Multi-agent Systems: Resource Allocation","Agent-based and Multi-agent Systems: Noncooperative Games","Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24347/file_24347.m3u8","length_sec":277,"provider":"hls"}],"references":[{"position":1,"raw":"[Andelman et al., 2007] Nir Andelman, Yossi Azar, and Motti Sorani. 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