Xiaohui Bei , Biaoshuai Tao , Jiajun Wu , Mingwei Yang
{"title":"The incentive guarantees behind Nash welfare in divisible resources allocation","authors":"Xiaohui Bei , Biaoshuai Tao , Jiajun Wu , Mingwei Yang","doi":"10.1016/j.artint.2025.104335","DOIUrl":null,"url":null,"abstract":"<div><div>We study the problem of allocating divisible resources among <em>n</em> agents, hopefully in a fair and efficient manner. With the presence of strategic agents, additional incentive guarantees are also necessary, and the problem of designing fair and efficient mechanisms becomes much less tractable. While there are flourishing positive results against strategic agents for homogeneous divisible items, very few of them are known to hold in cake cutting.</div><div>We show that the Maximum Nash Welfare (MNW) mechanism, which provides desirable fairness and efficiency guarantees and achieves an <em>incentive ratio</em> of 2 for homogeneous divisible items, also has an incentive ratio of 2 in cake cutting. Remarkably, this result holds even without the free disposal assumption, which is hard to get rid of in the design of truthful cake cutting mechanisms.</div><div>Moreover, we show that, for cake cutting, the Partial Allocation (PA) mechanism proposed by Cole et al. <span><span>[1]</span></span>, which is truthful and <span><math><mn>1</mn><mo>/</mo><mi>e</mi></math></span>-MNW for homogeneous divisible items, has an incentive ratio between <span><math><mo>[</mo><msup><mrow><mi>e</mi></mrow><mrow><mn>1</mn><mo>/</mo><mi>e</mi></mrow></msup><mo>,</mo><mi>e</mi><mo>]</mo></math></span> and when randomization is allowed, can be turned to be truthful in expectation. Given two alternatives for a trade-off between incentive ratio and Nash welfare provided by the MNW and PA mechanisms, we establish an interpolation between them for both cake cutting and homogeneous divisible items.</div><div>Finally, we study the optimal incentive ratio achievable by envy-free cake cutting mechanisms. We first give an envy-free mechanism for two agents with an incentive ratio of 4/3. Then, we show that any envy-free cake cutting mechanism with the connected pieces constraint has an incentive ratio of <span><math><mi>Θ</mi><mo>(</mo><mi>n</mi><mo>)</mo></math></span>.</div></div>","PeriodicalId":8434,"journal":{"name":"Artificial Intelligence","volume":"344 ","pages":"Article 104335"},"PeriodicalIF":5.1000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0004370225000542","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
We study the problem of allocating divisible resources among n agents, hopefully in a fair and efficient manner. With the presence of strategic agents, additional incentive guarantees are also necessary, and the problem of designing fair and efficient mechanisms becomes much less tractable. While there are flourishing positive results against strategic agents for homogeneous divisible items, very few of them are known to hold in cake cutting.
We show that the Maximum Nash Welfare (MNW) mechanism, which provides desirable fairness and efficiency guarantees and achieves an incentive ratio of 2 for homogeneous divisible items, also has an incentive ratio of 2 in cake cutting. Remarkably, this result holds even without the free disposal assumption, which is hard to get rid of in the design of truthful cake cutting mechanisms.
Moreover, we show that, for cake cutting, the Partial Allocation (PA) mechanism proposed by Cole et al. [1], which is truthful and -MNW for homogeneous divisible items, has an incentive ratio between and when randomization is allowed, can be turned to be truthful in expectation. Given two alternatives for a trade-off between incentive ratio and Nash welfare provided by the MNW and PA mechanisms, we establish an interpolation between them for both cake cutting and homogeneous divisible items.
Finally, we study the optimal incentive ratio achievable by envy-free cake cutting mechanisms. We first give an envy-free mechanism for two agents with an incentive ratio of 4/3. Then, we show that any envy-free cake cutting mechanism with the connected pieces constraint has an incentive ratio of .
期刊介绍:
The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.