ction that is currently estimated to have the highest value (\\( \pi(a \mid s) = \arg\max\_a Q(s,a) \\)), or with a probability \\(\epsilon\\) to take a random action to ensure some exploration. The Q-Learning update at each time step then had the following form:

$$
Q(s\_t, a\_t) \leftarrow Q(s\_t, a\_t) + \alpha \left[ r\_t + \gamma \max\_a Q(s\_{t+1}, a) - Q(s\_t, a\_t) \right]
$$

As mentioned, this equation is describing a regular Stochastic Gradient Descent update with learning rate \\(\alpha\\) and t