Thompson Sampling for Gaussian priors?

Hi!

I learned that mabwiser does not implement Thompson Sampling for Gaussian priors. As far as I know (please note that I’m quite new to multi-armed bandits), the Gaussian distribution is a conjugate prior and it’s possible to apply the procedure of Thompson Sampling on Gaussian priors. Would the maintainers be open to adding that as a learning policy? Or, is it the case that the optimality of Thompson sampling is only proved for Beta priors?

Thanks a lot!

[skadio]

@jaywonchung good luck with your submission! This of course takes high priority with or without mabwiser.

I am enjoying the technical brainstorming on the thread, and others might also find it useful. If it works out, especially it works well in your own experiments/paper, I would encourage the introduction of a new bandit as suggested.

We have a detailed write-up that shows a step-by-step intro to how to add a new bandit to mabwiser here https://fidelity.github.io/mabwiser/new_bandit.html. When you go that route, I can see us collaborating on the same PR --which might be fun! 😃

Good luck with your paper!

Serdar

[skadio]

Hope all is well, and your submission is now all good! Let’s us archive this issue now for future reference inc case it comes handy for others. Thank you again for the positive feedback!