terminal in agent.py seem not handle properly #60
Description
`
for self.step in tqdm(range(start_step, self.max_step), ncols=70, initial=start_step):
if self.step == self.learn_start:
num_game, self.update_count, ep_reward = 0, 0, 0.
total_reward, self.total_loss, self.total_q = 0., 0., 0.
ep_rewards, actions = [], []
# 1. predict
action = self.predict(self.history.get())
# 2. act
screen, reward, terminal = self.env.act(action, is_training=True)
# 3. observe
self.observe(screen, reward, action, terminal)
if terminal:
screen, reward, action, terminal = self.env.new_random_game()
num_game += 1
ep_rewards.append(ep_reward)
ep_reward = 0.
`
Function train in agent.py may not handle properly when the game is terminated. As the game is terminated, the new screen didn't add into history and memory, self.history isn't get updated. And in the next iteration, action = self.predict(self.history.get()) will be the same, i.e. terminated.