On submodular prophet inequalities and correlation gap

IF 0.9 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Theoretical Computer Science Pub Date : 2024-08-30 DOI:10.1016/j.tcs.2024.114814
Chandra Chekuri, Vasilis Livanos
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Abstract

Prophet inequalities and secretary problems have been extensively studied in recent years due to their elegance, connections to online algorithms, stochastic optimization, and mechanism design problems in game theoretic settings. Rubinstein and Singla [31] developed a notion of combinatorial prophet inequalities in order to generalize the standard prophet inequality setting to combinatorial valuation functions such as submodular and subadditive functions. For non-negative submodular functions they demonstrated a constant factor prophet inequality for matroid constraints. Along the way they showed a variant of the correlation gap for non-negative submodular functions.

In this paper we revisit their notion of correlation gap as well as the standard notion of correlation gap and prove much tighter and cleaner bounds. Via these bounds and other insights we obtain substantially improved constant factor combinatorial prophet inequalities for both monotone and non-monotone submodular functions over any constraint that admits an Online Contention Resolution Scheme. In addition to improved bounds we describe efficient polynomial-time algorithms that achieve these bounds.

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关于亚模态预言不等式和相关差距
先知不等式和秘书问题由于其优雅性、与在线算法的联系、随机优化以及博弈论环境中的机制设计问题,近年来得到了广泛的研究。Rubinstein 和 Singla [31] 提出了组合先知不等式的概念,以便将标准先知不等式设置推广到组合估值函数,如次模函数和次正函数。对于非负亚模态函数,他们证明了矩阵约束的常数因子先知不等式。在本文中,我们重温了他们的相关间隙概念以及相关间隙的标准概念,并证明了更严密、更简洁的边界。通过这些界限和其他见解,我们获得了大幅改进的常数因子组合先知不等式,适用于任何允许在线争议解决计划的约束条件下的单调和非单调亚模态函数。除了改进的边界,我们还描述了实现这些边界的高效多项式时间算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Theoretical Computer Science
Theoretical Computer Science 工程技术-计算机:理论方法
CiteScore
2.60
自引率
18.20%
发文量
471
审稿时长
12.6 months
期刊介绍: Theoretical Computer Science is mathematical and abstract in spirit, but it derives its motivation from practical and everyday computation. Its aim is to understand the nature of computation and, as a consequence of this understanding, provide more efficient methodologies. All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing.
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