MovieLen 100k with the original SafeOpt algorithm

[Lancial]

Hi there!

I'm trying to replicate the result of SafeOpt on the MovieLen 100k dataset and use it as a baseline for my class project. I tried to follow the procedure described in the paper but I failed to reproduce the result. Can I get some help? Thank you!

Here are the steps that I followed:

And here is my code:

The problem right now is that

• the algorithm breaks the safety constraint pretty quick (explored movies that have a 1.0 rating)
• the algorithm tends to be stuck at one or multiple high rating recommendations after some iterations and it is not able to generate novel results.
• similar to the second point, it explores only a small portion of the reachable set

We experimented with different std and noise variance but did not actually make significant improvement. I wonder do you notice any mistake we made in our code? In addition, would it be possible to share the code you used for the evaluation in the paper?

Thank you very much!

[ShivaprasadNadagoudr]

Try SafeOptSwarm class instead of SafeOpt for optimization, you'll get much better results