In policy gradients, is it possible to learn the policy if the chain of actions is selected and performed manually/externally (e.g. by myself or by someone else who I have no influence over)?
For example, we have four actions, and I choose in the beginning an action 2, and we end up in a given state, then I choose action 4 and we end up in another state, etc. (the actions can follow some logic or not but the question is general; some of the actions will end up with positive rewards).
Can we learn any meaningful policy network from such a chain of actions?