A3C Implementation

This is an attempt to implement the A3C algorithm in paper Asynchronous Methods for Deep Reinforcement Learning.

Author: Junyuan Xie (@piiswrong)

The algorithm should be mostly correct. However I cannot reproduce the result in the paper, possibly due to hyperparameter settings. If you can find a better set of parameters please propose a pull request.

Note this is a generalization of the original algorithm since we use batch_size threads for each worker instead of the original 1 thread.

Prerequisites

• Install OpenAI Gym: pip install gym
• Install the Atari Env: pip install gym[atari]
• You may need to install flask: pip install flask
• You may have to install cv2: pip install opencv-python

Usage

run python a3c.py --batch-size=32 --gpus=0 to run training on gpu 0 with batch-size=32.

run python launcher.py --gpus=0,1 -n 2 python a3c.py to launch training on 2 gpus (0 and 1), each gpu has two workers. Note: You might have to update the path to dmlc-core in launcher.py.