Pandora's Problem with Combinatorial Cost

Ben Berger, Tomer Ezra, M. Feldman, Federico Fusco
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引用次数: 2

Abstract

Pandora's problem is a fundamental model in economics that studies optimal search strategies under costly inspection. In this paper we initiate the study of Pandora's problem with combinatorial costs, capturing many real-life scenarios where search cost is non-additive. Weitzman's celebrated algorithm [1979] establishes the remarkable result that, for additive costs, the optimal search strategy is non-adaptive and computationally feasible. We inquire to which extent this structural and computational simplicity extends beyond additive cost functions. Our main result is that the class of submodular cost functions admits an optimal strategy that follows a fixed, non-adaptive order, thus preserving the structural simplicity of additive cost functions. In contrast, for the more general class of subadditive (or even XOS) cost functions the optimal strategy may already need to determine the search order adaptively. On the computational side, obtaining any approximation to the optimal utility requires super polynomially many queries to the cost function, even for a strict subclass of submodular cost functions. The full version of the paper is available at https://arxiv.org/abs/2303.01078.
潘多拉的组合成本问题
潘多拉问题(Pandora’s problem)是经济学中的一个基本模型,研究在代价高昂的检查下的最优搜索策略。在本文中,我们开始研究具有组合成本的潘多拉问题,捕获了许多搜索成本是非加性的现实场景。Weitzman著名的算法[1979]建立了一个显著的结果,即对于附加成本,最优搜索策略是非自适应的,并且在计算上是可行的。我们将探讨这种结构和计算的简单性在多大程度上超越了附加成本函数。我们的主要结果是,次模成本函数类允许遵循固定的、非自适应顺序的最优策略,从而保持了附加成本函数的结构简单性。相反,对于更一般的次加性(甚至XOS)代价函数,最优策略可能已经需要自适应地确定搜索顺序。在计算方面,获得任何最优效用的近似值都需要对代价函数进行超多项式的多次查询,即使是对子模代价函数的严格子类也是如此。该论文的完整版本可在https://arxiv.org/abs/2303.01078上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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