{"title":"Optimal Budget-Feasible Mechanisms for Additive Valuations","authors":"N. Gravin, Yaonan Jin, P. Lu, Chenhao Zhang","doi":"10.1145/3328526.3329586","DOIUrl":null,"url":null,"abstract":"In this paper, we obtain the tight approximation guarantees for budget-feasible mechanisms with an additive buyer. We propose a new simple randomized mechanism with an approximation ratio of $2$, improving the previous best known result of $3$. Our bound is tight with respect to either the optimal offline benchmark or its fractional relaxation. We also present a simple deterministic mechanism with the tight approximation guarantee of $3$ against the fractional optimum, improving the best known result of $(\\sqrt2 + 2)$ against the weaker integral benchmark.","PeriodicalId":416173,"journal":{"name":"Proceedings of the 2019 ACM Conference on Economics and Computation","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 ACM Conference on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3328526.3329586","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
In this paper, we obtain the tight approximation guarantees for budget-feasible mechanisms with an additive buyer. We propose a new simple randomized mechanism with an approximation ratio of $2$, improving the previous best known result of $3$. Our bound is tight with respect to either the optimal offline benchmark or its fractional relaxation. We also present a simple deterministic mechanism with the tight approximation guarantee of $3$ against the fractional optimum, improving the best known result of $(\sqrt2 + 2)$ against the weaker integral benchmark.