HandyRL VS pytorch-learn-reinforcement-learning

Compare HandyRL vs pytorch-learn-reinforcement-learning and see what are their differences.

HandyRL

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments. (by DeNA)

pytorch-learn-reinforcement-learning

A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc. (by gordicaleksa)
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HandyRL pytorch-learn-reinforcement-learning
1 3
282 139
0.0% -
4.3 0.0
12 days ago almost 3 years ago
Python Python
MIT License MIT License
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HandyRL

Posts with mentions or reviews of HandyRL. We have used some of these posts to build our list of alternatives and similar projects.

pytorch-learn-reinforcement-learning

Posts with mentions or reviews of pytorch-learn-reinforcement-learning. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing HandyRL and pytorch-learn-reinforcement-learning you can also consider the following projects:

adaptdl - Resource-adaptive cluster scheduler for deep learning training.

Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros