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@ppwwyyxx
Last active May 23, 2018 09:29
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placeholder for OpenAI Gym submission

Use A3C (asynchronous advantage actor-critic) written in TensorFlow. Training code, model & evaluation code at this repo

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@dylanthomas

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Wonderful. Thank YOU !

@Nhorning

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Hey, Kangaroo v.0 seems to get stuck over in the corner trying to catch things that fall until it gets killed. Is max session time already a training perimeter, and if not, do you think that could help in this case?

@lululun20

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Hey,
I just want to ask a very dumb question: I have read the a3c paper in which they kind of boasted for their good performance when running on a 16 core CPU. How come here we are talking about GPU...
Thank you in avance!

@ppwwyyxx

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It has better performance on GPU.

@cyrsis

cyrsis commented Dec 1, 2017

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[1201 10:47:55 @monitor.py:363] max_score: 863
[1201 10:47:55 @monitor.py:363] mean_score: 590.14

This is my first work out with GYM
Ran for 2 days with and stable , pretty good with single 1070 w8G Ram

it still running,

when I do

./train-atari.py --task gen_submit --load Breakout-v0.npy --env Breakout-v0 --output output_dir

It said

AssertionError: Breakout-v0.npy"

Do I need to wait for the training finish to get Breakout-v0.npy ????

@pablosjb

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Hello, i hope i am not bothering asking this here. I am kind of new here and I would like the following:

  • I am trying to solve the game "tennis-v0" in which the data (observation) is the image (RGB 3D-array) and I want first to extract features such as players position, ball position and score.
  • For the score, i am thinking about applying a text recognition algortihm in the region where the score is.
  • The problem is for the location of the items (players and ball), Can anyone help me telling which way to take?

Additionally I am preparing a dataset of the players in different shapes to then paste them in the field (previously the players erased) to have a classified dataset. What do you think about this.?? Thank you and regards.

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