Tensorflow implementation of [Human-Level Control through Deep Reinforcement Learning]
This implementation contains:
- Deep Q-network
- Experience replay memory
- to reduce the correlations between consecutive updates
- Network for Q-learning targets are fixed for intervals
- to reduce the correlations between target and predicted Q-values
- Python 3
- gym
- TensorFlow 1.8.0
- Tensorlayer 1.8.5
First, install prerequisites with:
$ pip install gym
$ pip install tensorlayer
To train a model:
$ python main.py
if you want to see the display, modify the code main.py
display = True
To see the train log in tensorboard:
$ tensorboard --logdir=./result/tensorboard
- Playing Atari with Deep Reinforcement Learning
- Human-level control through deep reinforcement learning
GPLv3