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Prophet inequalities are performance guarantees for online algorithms (a.k.a. stopping rules) solving the following "hiring problem": a decision maker sequentially inspects candidates whose values are independent random numbers and is asked…

Data Structures and Algorithms · Computer Science 2022-05-23 Makis Arsenis , Robert Kleinberg

Prophet inequalities compare online stopping strategies against an omniscient "prophet" using distributional knowledge. In this work, we augment this model with a conservative prediction of the maximum realized value. We quantify the…

Computer Science and Game Theory · Computer Science 2026-02-20 Johannes Brüstle , Ilan Reuven Cohen , Stefano Leonardi

We study the prophet inequality, a fundamental problem in online decision-making and optimal stopping, in a practical setting where rewards are observed only through noisy realizations and reward distributions are unknown. At each stage,…

Machine Learning · Statistics 2026-04-03 Jung-hun Kim , Vianney Perchet

In the Prophet Secretary problem, samples from a known set of probability distributions arrive one by one in a uniformly random order, and an algorithm must irrevocably pick one of the samples as soon as it arrives. The goal is to maximize…

Data Structures and Algorithms · Computer Science 2017-11-07 Yossi Azar , Ashish Chiplunkar , Haim Kaplan

We study the i.i.d. $k$-selection prophet inequality problem, where a decision-maker sequentially observes $n$ independent nonnegative rewards and may accept at most $k$ of them without knowledge of future realizations. The objective is to…

Optimization and Control · Mathematics 2026-02-24 Jieming Kong , Karthyek Murthy

In this work we initiate the study of buy-and-sell prophet inequalities. We start by considering what is arguably the most fundamental setting. In this setting the online algorithm observes a sequence of prices one after the other. At each…

Data Structures and Algorithms · Computer Science 2023-05-26 José Correa , Andrés Cristi , Paul Dütting , Mohammad Hajiaghayi , Jan Olkowski , Kevin Schewior

Optimal stopping theory is a powerful tool for analyzing scenarios such as online auctions in which we generally require optimizing an objective function over the space of stopping rules for an allocation process under uncertainty. Perhaps…

Computer Science and Game Theory · Computer Science 2015-10-16 Hossein Esfandiari , MohammadTaghi Hajiaghayi , Vahid Liaghat , Morteza Monemizadeh

In modern sample-driven Prophet Inequality, an adversary chooses a sequence of $n$ items with values $v_1, v_2, \ldots, v_n$ to be presented to a decision maker (DM). The process follows in two phases. In the first phase (sampling phase),…

Optimization and Control · Mathematics 2022-09-30 Krishnendu Chatterjee , Mona Mohammadi , Raimundo Saona

The I.I.D. Prophet Inequality is a fundamental problem where, given $n$ independent random variables $X_1,\dots,X_n$ drawn from a known distribution $\mathcal{D}$, one has to decide at every step $i$ whether to stop and accept $X_i$ or…

Computer Science and Game Theory · Computer Science 2024-12-02 Vasilis Livanos , Ruta Mehta

In the classical prophet inequality settings, a gambler is given a sequence of $n$ random variables $X_1, \dots, X_n$, taken from known distributions, observes their values in this (potentially adversarial) order, and select one of them,…

Computer Science and Game Theory · Computer Science 2024-04-19 Sariel Har-Peled , Elfarouk Harb , Vasilis Livanos

We study a variant of the single-choice prophet inequality problem where the decision-maker does not know the underlying distribution and has only access to a set of samples from the distributions. Rubinstein et al. [2020] showed that the…

Computer Science and Game Theory · Computer Science 2024-09-04 Tomer Ezra

The secretary problem or the game of Googol are classic models for online selection problems that have received significant attention in the last five decades. We consider a variant of the problem and explore its connections to data-driven…

Data Structures and Algorithms · Computer Science 2019-07-16 José Correa , Andrés Cristi , Boris Epstein , José A. Soto

We study a continuous and infinite time horizon counterpart to the classic prophet inequality, which we term the stationary prophet inequality problem. Here, copies of a good arrive and perish according to Poisson point processes. Buyers…

Data Structures and Algorithms · Computer Science 2021-07-23 Kristen Kessel , Amin Saberi , Ali Shameli , David Wajc

Prophet inequalities are a cornerstone in optimal stopping and online decision-making. Traditionally, they involve the sequential observation of $n$ non-negative independent random variables and face irrevocable accept-or-reject choices.…

Computer Science and Game Theory · Computer Science 2024-08-22 Sebastian Perez-Salazar , Victor Verdugo

We take a unifying approach to single selection optimal stopping problems with random arrival order and independent sampling of items. In the problem we consider, a decision maker (DM) initially gets to sample each of $N$ items…

Computer Science and Game Theory · Computer Science 2021-08-11 José Correa , Andrés Cristi , Boris Epstein , José Soto

Suppose a customer is faced with a sequence of fluctuating prices, such as for airfare or a product sold by a large online retailer. Given distributional information about what price they might face each day, how should they choose when to…

Data Structures and Algorithms · Computer Science 2019-10-10 Hossein Esfandiari , MohammadTaghi HajiAghayi , Brendan Lucier , Michael Mitzenmacher

We introduce a model of competing agents in a prophet setting, where rewards arrive online, and decisions are made immediately and irrevocably. The rewards are unknown from the outset, but they are drawn from a known probability…

Computer Science and Game Theory · Computer Science 2021-07-02 Tomer Ezra , Michal Feldman , Ron Kupfer

We study the single-choice Prophet Inequality problem when the gambler is given access to samples. We show that the optimal competitive ratio of $1/2$ can be achieved with a single sample from each distribution. When the distributions are…

Data Structures and Algorithms · Computer Science 2025-09-12 Aviad Rubinstein , Jack Z. Wang , S. Matthew Weinberg

Many online problems are studied in stochastic settings for which inputs are samples from a known distribution, given in advance, or from an unknown distribution. Such distributions model both beyond-worst-case inputs and, when given,…

Data Structures and Algorithms · Computer Science 2025-11-13 Gregory Kehne , Thomas Kesselheim

Hill and Kertz studied the prophet inequality on iid distributions [The Annals of Probability 1982]. They proved a theoretical bound of $1-\frac{1}{e}$ on the approximation factor of their algorithm. They conjectured that the best…

Data Structures and Algorithms · Computer Science 2017-06-01 Melika Abolhasani , Soheil Ehsani , Hosein Esfandiari , MohammadTaghi Hajiaghayi , Robert Kleinberg , Brendan Lucier