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项目作者： siddk

项目描述 ：
PyTorch Implementations of Standard Deep RL Algorithms (including REINFORCE, A2C, PPO)
高级语言： Python
项目地址: git://github.com/siddk/rl-kitchen-sink.git
创建时间： 2018-07-26T19:26:57Z
项目社区：https://github.com/siddk/rl-kitchen-sink
开源协议：
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Reinforcement Learning Kitchen Sink

PyTorch Implementations of Standard Deep RL Algorithms (including REINFORCE, A2C, PPO). Each of the below algorithms
are implemented for both OpenAI Gym Classic Control Tasks (e.g. Cartpole, MountainCar), as well as the Atari suite.

This repository exists mostly as a means to illustrate basic RL algorithms via extremely readable and well-documented
PyTorch implementations. This repository also stores hyperparameters and learning curves (with confidence intervals!)
for each task.

This code is inspired in equal parts from the OpenAI Baselines and Ilya
Kostrikov’s PyTorch-RL Repository.

REINFORCE

Advantage Actor-Critic (A2C)

Proximal Policy Optimization