Picking a random move in exploitation in Q-Learning I've been unsure about a principle of Q-Learning, I was hoping someone could clear it up.

When a new state is encountered, and thus there are no existing Q values, and that the algorithm decides to exploit, and not explore, how is the move chosen, since all the values are 0?

Is it chosen randomly? This intuitively would make sense, since after this, the state-move pair would have a value  and thus the matrix would get filled up throughout the iterations. But I just want to make sure I understand this correctly...

Thanks
It depends on the implementation of the software package that you are using. If you call a function that returns the maximum value and all values are the same then it might return the value at first index or some other one. The point is it doesn't matter which action is chosen since all of them are the best at the same time. So it's basically random but you should treat it as if you are trying to pick the best action.