rl_games VS Excolligere

Compare rl_games vs Excolligere and see what are their differences.

Excolligere

Forked Repo of J3soon's OmniIsaacGym-DofbotReacher (by DJT777)
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rl_games Excolligere
2 1
752 0
- -
5.3 10.0
about 20 hours ago about 1 year ago
Jupyter Notebook Python
MIT License GNU General Public License v3.0 or later
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.

rl_games

Posts with mentions or reviews of rl_games. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-17.

Excolligere

Posts with mentions or reviews of Excolligere. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-17.

What are some alternatives?

When comparing rl_games and Excolligere you can also consider the following projects:

OmniIsaacGymEnvs-DofbotReacher - Dofbot Reacher Reinforcement Learning Sim2Real Environment for Omniverse Isaac Gym/Sim

Practical_RL - A course in reinforcement learning in the wild

alpha-zero-general - A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

nn - 🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.