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arXiv · 2402.11084

The Competition Complexity of Prophet Inequalities

Johannes Brustle·José Correa·Paul Dütting·Tomer Ezra·Michal Feldman·Victor Verdugo
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Abstract

We study the classic single-choice prophet inequality problem through a resource augmentation lens. Our goal is to bound the $(1-\varepsilon)$-competition complexity of different types of online algorithms. This metric asks for the smallest $k$ such that the expected value of the online algorithm on $k$ copies of the original instance, is at least a $(1-\varepsilon)$-approximation to the expected offline optimum on a single copy. We show that block threshold algorithms, which set one threshold per copy, are optimal and give a tight bound of $k = \Theta(\log \log 1/\varepsilon)$. This shows that block threshold algorithms approach the offline optimum doubly-exponentially fast. For single threshold algorithms, we give a tight bound of $k = \Theta(\log 1/\varepsilon)$, establishing an exponential gap between block threshold algorithms and single threshold algorithms. Our model and results pave the way for exploring resource-augmented prophet inequalities in combinatorial settings. In line with this, we present preliminary findings for bipartite matching with one-sided vertex arrivals, as well as in XOS combinatorial auctions. Our results have a natural competition complexity interpretation in mechanism design and pricing applications.

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Johannes Brustle, José Correa, Paul Dütting, Tomer Ezra, Michal Feldman, Victor Verdugo. 2024-02-16. The Competition Complexity of Prophet Inequalities. https://arxiv.org/abs/2402.11084

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