资源分类
》 资源 》算法》Asynchronous Advantage Actor-Critic in PyTorch

Asynchronous Advantage Actor-Critic in PyTorch

2019-09-10 | |  145 |   0 |   0

Asynchronous Advantage Actor-Critic in PyTorch

This is PyTorch implementation of A3C as described in Asynchronous Methods for Deep Reinforcement Learning.

Since PyTorch has a easy method to control shared memory within multiprocess, we can easily implement asynchronous method like A3C.

Requirement

  • PyTorch 0.1.6

  • Python 3.5.2

  • gym 0.7.2

Usage

training

python run_a3c.py --atari

In default settings, num_process is 8. Set it as python run_a3c --num_process 4 to fit your number of cpu's cores.

test

After training

python test_a3c.py --render --monitor


上一篇：Monolingual and Multilingual Image Captioning

下一篇：ppo_pytorch_cpp

用户评价
全部评价

热门资源

  • TensorFlow-Course

    This repository aims to provide simple and read...

  • seetafaceJNI

    项目介绍 基于中科院seetaface2进行封装的JAVA...

  • mxnet_VanillaCNN

    This is a mxnet implementation of the Vanilla C...

  • DuReader_QANet_BiDAF

    Machine Reading Comprehension on DuReader Usin...

  • Klukshu-Sockeye-...

    KLUKSHU SOCKEYE PROJECTS 2016 This repositor...