《强盗》中的因果关系:一项调查

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Chandrasekar Subramanian, Balaraman Ravindran
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引用次数: 0

摘要

关于强盗的文献在很大程度上独立于因果推理的进展而发展。在过去的几年里,人们开始研究这两个领域之间的密切联系,并产生了富有成效的想法,这些想法推动了强盗算法的发展。我们提出了第一个调查,专门关注这两个领域的交集。我们首先为这一领域的研究提供了一个分类,然后将重要的工作放在这个结构中。我们还描述了各种算法和方法,并提供了重点。最后,对未来的研究方向进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Causality in Bandits: A Survey
The literature on bandits has developed largely independently of advances in causal inference. Work in the last few years has started investigating the close connections between these two areas and that has led to fruitful ideas that have produced advances in bandit algorithms. We present the first survey focusing specifically on the intersection of these two areas. We first provide a taxonomy for categorizing research in this area, and then place important works within this structure. We also describe various algorithms and methods, and provide the highlights. Finally, we point out promising directions for future research in this area.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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