[REQUEST] Support for additional OPE algorithms

[LXYTSOS]

Support for additional OPE algorithms such as weighted importance sampling, doubly robust.

[pathway]

Gawd yes please

[takuseno]

@LXYTSOS Thank you for the issue! Those should definitely be supported for the practical usecases. I'll consider this feature in the following updates.

[paulhilders]

@takuseno This would be a very useful addition to an already amazing library! Do you maybe have an indication of when these features might be added?

[joshuaspear]

Hey - I have started creating an ope library for offline RL which includes an api for d3rlpy. It's not fully tested yet but I have included regression (weighted importance sampling). I have also included functionality to have ope methods as scorers when calling LearnableBase.fit in d3rlpy. However, this relies on an epoch callback functionality that I have implemented in the following PR (#286). Feedback and contributions are more than welcome :)

https://github.com/joshuaspear/offline_rl_ope