policy-gradient-pong

Reinforcement learning approach to win Atari game pong.

tensorflow implementation of Andrej Karpathy's original numpy version.

dependencies

• tensorflow
• numpy
• openai gym

usage

train:

python policy_gradient_pong.py

demo:

python policy_gradient_pong_demo.py <checkpoint path>

we provide trained weights in the folder weight/ which can beat computer with high probability.

notice

It takes very long time, about 90 hours on a dell RX 730 with a Intel(R) Xeon(R) CPU E5-2603 v3 @ 1.60GHz 8 cores CPU, 16G RAM and a gtx 1080ti GPU, to win computer by 5 scores.

It takes much shorter time to train on a 2016 mac book pro without GPU. So i think much of the time spent on simulation, rather than network forward and backward.

training progress