Dynamic Online Pricing with Incomplete Information Using Multiarmed Bandit Experiments
提出一种将多臂赌博机算法与微观经济选择理论结合的动态定价实验策略，用于在不完全信息下优化在线定价。
We propose an alternative dynamic price experimentation policy that extends multiarmed bandit (MAB) algorithms from statistical machine learning to include microeconomic choice theory.