[gajomi]

It seems to me that they are basically describing a variational formulation of the "optimization perspective" of reinforcement learning, which is cool, but I am confused... where is the supervised learning? Like what is the input and what is the output?

[bnegreve]

The way I understand it, the two subproblems are supervised in the sense that they are trained using data sampled from a fixed distribution, instead of data sampled from a distribution that changes as you update your model, as it is usually the case in RL. This makes the training more stable.

[jonnycomputer]

Thanks for clarifying that point.

[Cmmn_Dscndnt]

It seems more as if the authors are abusing terms from Machine Learning like "Supervised Learning".

[jonnycomputer]

abusing how?