ElegantRL VS machin

Compare ElegantRL vs machin and see what are their differences.

machin

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ... (by iffiX)
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ElegantRL machin
6 2
3,376 381
2.4% -
7.4 1.8
5 days ago over 2 years ago
Python Python
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ElegantRL

Posts with mentions or reviews of ElegantRL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-15.

machin

Posts with mentions or reviews of machin. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-30.

What are some alternatives?

When comparing ElegantRL and machin you can also consider the following projects:

stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

tianshou - An elegant PyTorch deep reinforcement learning library.

minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Deep-Reinforcement-Learning-Algorithms - 32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

pytorch-ddpg - Deep deterministic policy gradient (DDPG) in PyTorch 🚀

Apache Impala - Apache Impala

RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

dcss-ai-wrapper - An API for Dungeon Crawl Stone Soup for Artificial Intelligence research.