TY - GEN

T1 - Pandora's Problem with Combinatorial Cost

AU - Berger, Ben

AU - Ezra, Tomer

AU - Feldman, Michal

AU - Fusco, Federico

N1 - Publisher Copyright:
© 2023 ACM.

PY - 2023/7/9

Y1 - 2023/7/9

N2 - 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.

AB - 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.

KW - pandora's box problem

KW - pandora's problem

UR - http://www.scopus.com/inward/record.url?scp=85168099880&partnerID=8YFLogxK

U2 - 10.1145/3580507.3597699

DO - 10.1145/3580507.3597699

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AN - SCOPUS:85168099880

T3 - EC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation

SP - 273

EP - 292

BT - EC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation

PB - Association for Computing Machinery, Inc

T2 - 24th ACM Conference on Economics and Computation, EC 2023

Y2 - 9 July 2023 through 12 July 2023

ER -