Viewing results of gameplay? about deep-q-learning-paper-to-code HOT 3 CLOSED

Managed to solve this by introducing an array into the preprocessFrame wrapper into itself for evaluation purposes! But an official approach would be welcome!

from deep-q-learning-paper-to-code.

Check out lecture #39. I show how to save video of the agent playing the game, and it renders with the original frames (not our grayscale / downsized images).

from deep-q-learning-paper-to-code.

Thank you Phil,

You'll find my adaptation for your code for Doom here
https://github.com/EXJUSTICE/Doom_DQN_GC/tree/master/PytorchDQN

Will you be doing a course on policy gradient models? Or is the Actor Critic course sufficient to cover the area in your opinion?

Also, I notice that that in DDQN, you specify that we must calculate S (t+1) through the eval and target networks, in this case S (t+1) is a state action value, correct? , as you do end up calling T.argmax() on it later.

from deep-q-learning-paper-to-code.