Skip to content
This repository has been archived by the owner on Apr 25, 2023. It is now read-only.

k frame #20

Open
fi000 opened this issue Sep 4, 2018 · 0 comments
Open

k frame #20

fi000 opened this issue Sep 4, 2018 · 0 comments

Comments

@fi000
Copy link

fi000 commented Sep 4, 2018

@keon Thanks for your applicable code just one question how we can add K frame to this as said in section 4.1 last sentences of first paragraph of Mnih et al. Nature 2015
4.1 Preprocessing and Model Architecture
Working directly with raw Atari frames, which are 210 � 160 pixel images with a 128 color palette,
can be computationally demanding, so we apply a basic preprocessing step aimed at reducing the
input dimensionality. The raw frames are preprocessed by first converting their RGB representation
to gray-scale and down-sampling it to a 110 �84 image. The final input representation is obtained by
cropping an 84 � 84 region of the image that roughly captures the playing area. The final cropping
stage is only required because we use the GPU implementation of 2D convolutions from [11], which
expects square inputs. For the experiments in this paper, the function � from algorithm 1 applies this
preprocessing to the last 4 frames of a history and stacks them to produce the input to the Q-function.

Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant