@inproceedings{
tang2024intrinsic,
title={Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling},
author={Wei Tang and Haifeng Xu and Ruimin Zhang and Derek Zhu},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=Mmcy1p15Hc}
}
Prophet inequality concerns a basic optimal stopping problem and states that simple threshold stopping policies --- i.e., accepting the first reward larger than a certain threshold --- can achieve tight $\frac{1}{2}$-approximation to the optimal prophet value. Motivated by its economic applications, this paper studies the robustness of this approximation to natural strategic manipulations in which each random reward is associated with a self-interested player who may selectively reveal his realized reward to the searcher in order to maximize his probability of being selected. 

We say a threshold policy is $\alpha$(-strategically)-robust if it (a) achieves the  $\alpha$-approximation to the prophet value for strategic players; and (b) meanwhile remains a  $\frac{1}{2}$-approximation in the standard non-strategic setting.
Starting with a characterization of each player's optimal information revealing strategy, we demonstrate the intrinsic robustness of prophet inequalities to strategic reward signaling through the following results:
(1) for arbitrary reward distributions, there is a threshold policy that is $\frac{1-\frac{1}{e}}{2}$-robust, and this ratio is tight;
(2) for i.i.d. reward distributions, there is a threshold policy that is $\frac{1}{2}$-robust, which is tight for the setting; 
and (3) for log-concave (but non-identical) reward distributions, the $\frac{1}{2}$-robustness can also be achieved under certain regularity assumptions.
Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling
Wei Tang Haifeng Xu Ruimin Zhang Derek Zhu