Single-Sample Prophet Inequalities via Greedy-Ordered Selection

Fuente: arXiv
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Main Authors: Caramanis, Constantine, Dütting, Paul, Faw, Matthew, Fusco, Federico, Lazos, Philip, Leonardi, Stefano, Papadigenopoulos, Orestis, Pountourakis, Emmanouil, Reiffenhäuser, Rebecca
Format: Preprint
Published: 2021
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author Caramanis, Constantine
Dütting, Paul
Faw, Matthew
Fusco, Federico
Lazos, Philip
Leonardi, Stefano
Papadigenopoulos, Orestis
Pountourakis, Emmanouil
Reiffenhäuser, Rebecca
author_facet Caramanis, Constantine
Dütting, Paul
Faw, Matthew
Fusco, Federico
Lazos, Philip
Leonardi, Stefano
Papadigenopoulos, Orestis
Pountourakis, Emmanouil
Reiffenhäuser, Rebecca
contents We study single-sample prophet inequalities (SSPIs), i.e., prophet inequalities where only a single sample from each prior distribution is available. Besides a direct, and optimal, SSPI for the basic single choice problem [Rubinstein et al., 2020], most existing SSPI results were obtained via an elegant, but inherently lossy, reduction to order-oblivious secretary (OOS) policies [Azar et al., 2014]. Motivated by this discrepancy, we develop an intuitive and versatile greedy-based technique that yields SSPIs directly rather than through the reduction to OOSs. Our results can be seen as generalizing and unifying a number of existing results in the area of prophet and secretary problems. Our algorithms significantly improve on the competitive guarantees for a number of interesting scenarios (including general matching with edge arrivals, bipartite matching with vertex arrivals, and certain matroids), and capture new settings (such as budget additive combinatorial auctions). Complementing our algorithmic results, we also consider mechanism design variants. Finally, we analyze the power and limitations of different SSPI approaches by providing a partial converse to the reduction from SSPI to OOS given by Azar et al.
format Preprint
id arxiv_https___arxiv_org_abs_2111_03174
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Single-Sample Prophet Inequalities via Greedy-Ordered Selection
Caramanis, Constantine
Dütting, Paul
Faw, Matthew
Fusco, Federico
Lazos, Philip
Leonardi, Stefano
Papadigenopoulos, Orestis
Pountourakis, Emmanouil
Reiffenhäuser, Rebecca
Data Structures and Algorithms
Computer Science and Game Theory
We study single-sample prophet inequalities (SSPIs), i.e., prophet inequalities where only a single sample from each prior distribution is available. Besides a direct, and optimal, SSPI for the basic single choice problem [Rubinstein et al., 2020], most existing SSPI results were obtained via an elegant, but inherently lossy, reduction to order-oblivious secretary (OOS) policies [Azar et al., 2014]. Motivated by this discrepancy, we develop an intuitive and versatile greedy-based technique that yields SSPIs directly rather than through the reduction to OOSs. Our results can be seen as generalizing and unifying a number of existing results in the area of prophet and secretary problems. Our algorithms significantly improve on the competitive guarantees for a number of interesting scenarios (including general matching with edge arrivals, bipartite matching with vertex arrivals, and certain matroids), and capture new settings (such as budget additive combinatorial auctions). Complementing our algorithmic results, we also consider mechanism design variants. Finally, we analyze the power and limitations of different SSPI approaches by providing a partial converse to the reduction from SSPI to OOS given by Azar et al.
title Single-Sample Prophet Inequalities via Greedy-Ordered Selection
topic Data Structures and Algorithms
Computer Science and Game Theory
url https://arxiv.org/abs/2111.03174