Comment by crazygringo
Comment by crazygringo 6 days ago
I'm not talking about the literature -- I'm talking about the extremely simplistic and sub-optimal procedure described in the post.
If you want to get sophisticated, MAB properly done is essentially just A/B testing with optimal strategies for deciding when to end individual A/B tests, or balancing tests optimally for a limited number of trials. But again, it doesn't "beat" A/B testing -- it is A/B testing in that sense.
And that's what I mean. You can't magically increase your reward while simultaneously getting statistically significant results. Either your results are significant to a desired level or not, and there's no getting around the number of samples you need to achieve that.
I am talking about the literature which solves MAB in a variety of ways, including the one in the post.
> MAB properly done is essentially just A/B testing
Words are only useful insofar as their meanings invoke ideas, and in my experience absolutely no one thinks of other MAB strategies when someone talks about A/B testing.
Sure, you can classify A/B testing as one extremely suboptimal approach to solving MAB problem. This classification doesn’t help much though, because the other MAB techniques do “magically increase the rewards” compared this simple technique.