[ertdfgcvb]

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

[sweezyjeezy]

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.

[zeroCalories]

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.

[lern_too_spel]

Yes.