placeholder for OpenAI Gym submission

tensorpack-gym.md

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

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Yes I mentioned these differences. The number of actions also make it harder in gym.
For the result here I use deepmind settings and for gym submissions I used gym.

Wonderful. Thank YOU !

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?

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!

It has better performance on GPU.

[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 ????

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.