Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making
序贯决策中用于高效政策评估的最优处理分配
A/B testing is critical for modern technological companies to evaluate the effectiveness of newly developed products against standard baselines. This paper studies optimal designs that aim to maximize the amount of information obtained from online experiments to estimate treatment effects accurately. We propose three optimal allocation strategies in a dynamic setting where treatments are sequentially assigned over time. These strategies are designed to minimize the variance…