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arxiv: 2107.00680 · v1 · pith:BEVP4CZRnew · submitted 2021-07-01 · 💻 cs.LG

A Map of Bandits for E-commerce

classification 💻 cs.LG
keywords algorithmsbanditapplicationsbanditsfindfocusoftenaction
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The rich body of Bandit literature not only offers a diverse toolbox of algorithms, but also makes it hard for a practitioner to find the right solution to solve the problem at hand. Typical textbooks on Bandits focus on designing and analyzing algorithms, and surveys on applications often present a list of individual applications. While these are valuable resources, there exists a gap in mapping applications to appropriate Bandit algorithms. In this paper, we aim to reduce this gap with a structured map of Bandits to help practitioners navigate to find relevant and practical Bandit algorithms. Instead of providing a comprehensive overview, we focus on a small number of key decision points related to reward, action, and features, which often affect how Bandit algorithms are chosen in practice.

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