LGAug 13, 2015

A Survey on Contextual Multi-armed Bandits

arXiv:1508.03326v2141 citations
AI Analysis

This is an incremental survey paper for researchers in reinforcement learning and decision-making.

This survey paper reviews stochastic and adversarial contextual bandit algorithms, analyzing their assumptions and regret bounds.

In this survey we cover a few stochastic and adversarial contextual bandit algorithms. We analyze each algorithm's assumption and regret bound.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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