def select_action(self, state):
        best_action = nonzero(self.Q_mat[state]==max(self.Q_mat[state]))[0]
        return best_action[random.randint(0,len(best_action))] if random.random() < .9 else random.randint(0,self.num_actions)
dataset/ETHPy150Open posborne/mlcollection/mlcollection/lib/reinforcement/simple_rl.py/Simple_RL.select_action/original