Comments (3)
I gave it a try. The animation is there, but my code always outputs the same decision (7 in my case). I am still beginning, so if anybody has some suggestions, let me know.
def display_game_play(model_path, n_max_steps = 2000):
env = gym.make('MsPacman-v0')
obs = env.reset()
with tf.Session() as sess:
saver.restore(sess, model_path)
for step in range(n_max_steps):
#evaluate what to do
state = preprocess_observation(obs)
q_values = critic_q_values.eval(feed_dict={X_state: [state]}) #maybe actor_q_values?
action_val = np.argmax(q_values)
print("\rstep: {}, action_val: {}".format(step, action_val), end="")
obs, reward, done, info = env.step(action_val)
env.render()
if done:
print("DONE - FAILED")
break
env.close()
return
save_path = "./data/ch16/my_dqn.ckpt"
display_game_play(save_path)
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Hi @StrangeTcy ,
That's a great suggestion! 👍 I am adding this to my To-Do list (however, adding the solutions to the exercises of all chapters is higher priority and quite time consuming, so I can't promise I'll do this very soon).
Thanks!
Aurélien
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I added test code after training in chapter 16, so you can now view Ms Pacman learning to play. Thanks for the great suggestion!
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