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Comment by ertdfgcvb

5 days ago

I don't follow. In this case would sampling 50/50 always give better/unbiased results on the experiment?

Sampling 50/50 will always give you the best chance of picking the best ultimate 'winner' in a fixed time horizon, at the cost of only sampling the winning variant 50% of the time. That's true if the reward rates are fixed or not. But some changes in reward rates will also cause MAB aggregate statistics to skew in a way that they shouldn't for a 50/50 split yeah.

  • What do you think of using the epsilon-first approach then? We could explore for that fixed time horizon, then start choosing greedy after that. I feel like the only downside is that adding new arms becomes more complicated.

    • What percent of companies using A/B testing do you think know what the Texas Sharpshooter is and how to identify it, let alone what epsilon is or what it means?