An Empirical Evaluation of Thompson Sampling

作者：Olivier Chapelle, Lihong Li · 年份：2011 · 被引用次数：1002 · 研究领域：Advanced Bandit Algorithms Research、Machine Learning and Algorithms、Optimization and Search Problems

Thompson sampling is one of oldest heuristic to address the exploration / ex-ploitation trade-off, but it is surprisingly unpopular in the literature. We present here some empirical results using Thompson sampling on simulated and real data, and show that it is highly competitive. And since this heuristic is very easy to implement, we argue that it should be part of the standard baselines to compare against. 1