def select_action(self, q_values):
assert q_values.ndim == <NUM_LIT:1><EOL>nb_actions = q_values.shape[<NUM_LIT:0>]<EOL>if np.random.uniform() < self.eps:<EOL><INDENT>action = np.random.randint(<NUM_LIT:0>, nb_actions)<EOL><DEDENT>else:<EOL><INDENT>action = np.argmax(q_values)<EOL><DEDENT>return action<EOL>
Return the selected action

        # Arguments
            q_values (np.ndarray): List of the estimations of Q for each action

        # Returns
            Selection action