def select_action(self, q_values):
assert q_values.ndim == <NUM_LIT:1><EOL>q_values = q_values.astype('<STR_LIT>')<EOL>nb_actions = q_values.shape[<NUM_LIT:0>]<EOL>exp_values = np.exp(np.clip(q_values / self.tau, self.clip[<NUM_LIT:0>], self.clip[<NUM_LIT:1>]))<EOL>probs = exp_values / np.sum(exp_values)<EOL>action = np.random.choice(range(nb_actions), p=probs)<EOL>return action<EOL>
Return the selected action

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

        # Returns
            Selection action