{"title":"Pandora's Problem with Nonobligatory Inspection","authors":"Hedyeh Beyhaghi, Robert D. Kleinberg","doi":"10.1145/3328526.3329626","DOIUrl":null,"url":null,"abstract":"Martin Weitzman's \"Pandora's problem\" furnishes the mathematical basis for optimal search theory in economics. Nearly 40 years later, Laura Doval introduced a version of the problem in which the searcher is not obligated to pay the cost of inspecting an alternative's value before selecting it. Unlike the original Pandora's problem, the version with nonobligatory inspection cannot be solved optimally by any simple ranking-based policy, and it is unknown whether there exists any polynomial-time algorithm to compute the optimal policy. This motivates the study of approximately optimal policies that are simple and computationally efficient. In this work we provide the first non-trivial approximation guarantees for this problem. We introduce a family of \"committing policies\" such that it is computationally easy to find and implement the optimal committing policy. We prove that the optimal committing policy is guaranteed to approximate the fully optimal policy within a 1-1/e = 0.63... factor, and for the special case of two boxes we improve this factor to 4/5 and show that this approximation is tight for the class of committing policies.","PeriodicalId":416173,"journal":{"name":"Proceedings of the 2019 ACM Conference on Economics and Computation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 ACM Conference on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3328526.3329626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24
Abstract
Martin Weitzman's "Pandora's problem" furnishes the mathematical basis for optimal search theory in economics. Nearly 40 years later, Laura Doval introduced a version of the problem in which the searcher is not obligated to pay the cost of inspecting an alternative's value before selecting it. Unlike the original Pandora's problem, the version with nonobligatory inspection cannot be solved optimally by any simple ranking-based policy, and it is unknown whether there exists any polynomial-time algorithm to compute the optimal policy. This motivates the study of approximately optimal policies that are simple and computationally efficient. In this work we provide the first non-trivial approximation guarantees for this problem. We introduce a family of "committing policies" such that it is computationally easy to find and implement the optimal committing policy. We prove that the optimal committing policy is guaranteed to approximate the fully optimal policy within a 1-1/e = 0.63... factor, and for the special case of two boxes we improve this factor to 4/5 and show that this approximation is tight for the class of committing policies.
Martin Weitzman的“潘多拉问题”为经济学中的最优搜索理论提供了数学基础。近40年后,劳拉·多瓦尔(Laura Doval)提出了这个问题的另一个版本,即搜索者在选择备选项之前没有义务支付检查备选项价值的费用。与原始的潘多拉问题不同,非强制检查版本不能通过任何简单的基于排名的策略来最优解决,并且不知道是否存在多项式时间算法来计算最优策略。这激发了对简单且计算效率高的近似最优策略的研究。在这项工作中,我们为这个问题提供了第一个非平凡近似保证。我们引入了一系列“提交策略”,以便在计算上容易找到并实现最优提交策略。我们证明了最优提交策略在1-1/e = 0.63范围内保证近似于完全最优策略。因子,对于两个盒子的特殊情况,我们将这个因子提高到4/5,并表明这个近似对于提交策略类是紧密的。