We study a pricing problem where a seller has $k$ identical copies of a product, buyers arrive sequentially, and the seller prices the items aiming to maximize social welfare. When $k=1$, this is the so called "prophet inequality" problem for which there is a simple pricing scheme achieving a competitive ratio of $1/2$. On the other end of the spectrum, as $k$ goes to infinity, the asymptotic performance of both static and adaptive pricing is well understood.
We provide a static pricing scheme for the small-supply regime: where $k$ is small but larger than $1$. Prior to our work, the best competitive ratio known for this setting was the $1/2$ that follows from the single-unit prophet inequality. Our pricing scheme is easy to describe as well as practical -- it is anonymous, non-adaptive, and order-oblivious. We pick a single price that equalizes the expected fraction of items sold and the probability that the supply does not sell out before all customers are served; this price is then offered to each customer while supply lasts. This extends an approach introduced by Samuel-Cahn for the case of $k=1$. This pricing scheme achieves a competitive ratio that increases gradually with the supply. Subsequent work by Jiang, Ma, and Zhang shows that our pricing scheme is the optimal static pricing for every value of $k$.
The prophet inequalities problem has received significant study over the past decades and has several applications such as to online auctions. In this paper, we study two variants of the i.i.d. prophet inequalities problem, namely the windowed prophet inequalities problem and the batched prophet inequalities problem. For the windowed prophet inequalities problem, we show that for window size $o(n)$, the optimal competitive ratio is $α\approx 0.745$, the same as in the non-windowed case. In the case where the window size is $n/k$ for some constant $k$, we show that $α_k < WIN_{n/k} \le α_k + o_…
We investigate non-adaptive algorithms for matroid prophet inequalities. Matroid prophet inequalities have been considered resolved since 2012 when [KW12] introduced thresholds that guarantee a tight 2-approximation to the prophet; however, this algorithm is adaptive. Other approaches of [CHMS10] and [FSZ16] have used non-adaptive thresholds with a feasibility restriction; however, this translates to adaptively changing an item's threshold to infinity when it cannot be taken with respect to the additional feasibility constraint, hence the algorithm is not truly non-adaptive. A major applicatio…
We consider the prophet inequality problem for (not necessarily bipartite) matching problems with independent edge values, under both edge arrivals and vertex arrivals. We show constant-factor prophet inequalities for the case where the online algorithm has only limited access to the value distributions through samples. First, we give a $16$-approximate prophet inequality for matching in general graphs under edge arrivals that uses only a single sample from each value distribution as prior information. Then, for bipartite matching and (one-sided) vertex arrivals, we show an improved bound of $…
We introduce a new decomposition technique for random variables that maps a generic instance of the prophet inequalities problem to a new instance where all but a constant number of variables have a tractable structure that we refer to as $(\varepsilon, δ)$-smallness. Using this technique, we make progress on several outstanding problems in the area: - We show that, even in the case of non-identical distributions, it is possible to achieve (arbitrarily close to) the optimal approximation ratio of $β\approx 0.745$ as long as we are allowed to remove a small constant number of distributions. - W…
在经典的预言不等式中，赌徒观察到一系列随机奖励$V_1,...,V_n$，并且必须决定，对于每一个奖励$V_i$，是保留它并停止游戏，还是永远放弃奖励并显示下一个值$V_i$。赌徒的目标是获得最佳离线算法将获得的预期奖励的恒定分数。最近，预言家不等式已经被推广到赌徒可以选择$k$项目的设置，更一般地说，他可以选择拟阵中的任何独立集。然而，所有现有的算法都要求赌徒知道从中提取奖励$V_1,...,V_n$的分布。假设赌徒知道从中抽取$V_1,...,V_n$的分布是非常强的。相反，我们使用更简单的假设，即赌徒只知道这个分布中的几个样本。我们构造了第一个单样本预言不等式的许多设置的兴趣，其保证都匹配最好的可能渐近，\emph{even with full knowledge of the distribution}。具体而言，我们提供了一种新的单样本算法时，赌徒可以选择任何$k$元素的分析是基于有限相关的随机游走。此外，我们提供了一个黑盒方法转换特定类型的解决方案，相关的\emph{secretary problem}单样本先知不等式，并将其应用到现有的几个算法。最后，我们给出了常度二部匹配的常样本预言不等式。我们将这些结果应用于设计一次标价和多维拍卖机制与有限的信息设置与非对称投标人。
We consider prophet inequalities for XOS and MPH-$k$ combinatorial auctions and give a simplified proof for the existence of static and anonymous item prices which recover the state-of-the-art competitive ratios. Our proofs make use of a linear programming formulation which has a non-negative objective value if there are prices which admit a given competitive ratio $α\geq 1$. Changing our perspective to dual space by an application of strong LP duality, we use an interpretation of the dual variables as probabilities to directly obtain our result. In contrast to previous work, our proofs do not…
We consider prophet inequalities subject to feasibility constraints that are the intersection of $q$ matroids. The best-known algorithms achieve a $Θ(q)$-approximation, even when restricted to instances that are the intersection of $q$ partition matroids, and with i.i.d.~Bernoulli random variables. The previous best-known lower bound is $Θ(\sqrt{q})$ due to a simple construction of [Kleinberg-Weinberg STOC 2012] (which uses i.i.d.~Bernoulli random variables, and writes the construction as the intersection of partition matroids). We establish an improved lower bound of $q^{1/2+Ω(1/\log \log q)}…
Prophet inequalities for rewards maximization are fundamental to optimal stopping theory with extensive applications to mechanism design and online optimization. We study the \emph{cost minimization} counterpart of the classical prophet inequality: a decision maker is facing a sequence of costs $X_1, X_2, \dots, X_n$ drawn from known distributions in an online manner and \emph{must} ``stop'' at some point and take the last cost seen. The goal is to compete with a ``prophet'' who can see the realizations of all $X_i$'s upfront and always select the minimum, obtaining a cost of $\mathbb{E}[\min_…
The study of the prophet inequality problem in the limited information regime was initiated by Azar et al. [SODA'14] in the pursuit of prior-independent posted-price mechanisms. As they show, $O(1)$-competitive policies are achievable using only a single sample from the distribution of each agent. A notable portion of their results relies on reducing the design of single-sample prophet inequalities (SSPIs) to that of order-oblivious secretary (OOS) policies. The above reduction comes at the cost of not fully utilizing the available samples. However, to date, this is essentially the only method…
We design novel mechanisms for welfare-maximization in two-sided markets. That is, there are buyers willing to purchase items and sellers holding items initially, both acting rationally and strategically in order to maximize utility. Our mechanisms are designed based on a powerful correspondence between two-sided markets and prophet inequalities. They satisfy individual rationality, dominant-strategy incentive compatibility, budget-balance constraints and give constant-factor approximations to the optimal social welfare. We improve previous results in several settings: Our main focus is on mat…
Threshold Dynamics and Correlated Prophet Inequalities
Universidad de Chile（智利大学）；TNG Technology Consulting（TNG技术咨询）；Moroccan Center for Game Theory, Université Mohammed VI Polytechnique（摩洛哥博弈论中心，穆罕默德六世polytechnique大学）；Center for Mathematical Modeling & Department of Computer Science, University of Southern California（南加州大学数学建模中心与计算机科学系）；Department of Mathematics and Computer Science, University of Cologne（科隆大学数学与计算机科学系）；Institute for Mathematical and Computational Engineering, and Department of Industrial and Systems Engineering, Pontificia Universidad Católica de Chile（天主教智利大学数学与计算工程研究所及工业与系统工程系）
Competition Versus Complexity in Multiple-Selection Prophet Inequalities
Pontificia Universidad Católica de Chile（智利天主教 Pontificia 大学）；Rice University（莱斯大学）；Ken Kennedy Institute, Rice University（莱斯大学肯·肯尼迪研究所）；Institute for Mathematical and Computational Engineering, Pontificia Universidad Católica de Chile（智利天主教 Pontificia 大学数学与计算工程研究所）；Department of Industrial and Systems Engineering, Pontificia Universidad Católica de Chile（智利天主教 Pontificia 大学工业与系统工程系）
A central object in optimal stopping theory is the single-choice prophet inequality for independent, identically distributed random variables: Given a sequence of random variables $X_1,\dots,X_n$ drawn independently from a distribution $F$, the goal is to choose a stopping time $τ$ so as to maximize $α$ such that for all distributions $F$ we have $\mathbb{E}[X_τ] \geq α\cdot \mathbb{E}[\max_tX_t]$. What makes this problem challenging is that the decision whether $τ=t$ may only depend on the values of the random variables $X_1,\dots,X_t$ and on the distribution $F$. For quite some time the best…
IIIS, Tsinghua University（清华大学交叉信息研究院）；ITCS, Shanghai University of Finance and Economics（上海财经大学理论计算机科学中心）
This paper explores a theory of generalization for learning problems on product distributions, complementing the existing learning theories in the sense that it does not rely on any complexity measures of the hypothesis classes. The main contributions are two general sample complexity bounds: (1) $\tilde{O} \big( \frac{nk}{ε^2} \big)$ samples are sufficient and necessary for learning an $ε$-optimal hypothesis in any problem on an $n$-dimensional product distribution, whose marginals have finite supports of sizes at most $k$; (2) $\tilde{O} \big( \frac{n}{ε^2} \big)$ samples are sufficient and …
Matching and pricing are two critical levers in two-sided marketplaces to connect demand and supply. The platform can produce more efficient matching and pricing decisions by batching the demand requests. We initiate the study of the two-stage stochastic matching problem, with or without pricing, to enable the platform to make improved decisions in a batch with an eye toward the imminent future demand requests. This problem is motivated in part by applications in online marketplaces such as ride hailing platforms. We design online competitive algorithms for vertex-weighted (or unweighted) two-…
