Simple-MADRL-Chess
machin
Simple-MADRL-Chess | machin | |
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1 | 2 | |
10 | 389 | |
- | - | |
7.2 | 1.8 | |
about 1 year ago | almost 3 years ago | |
Python | Python | |
MIT License | MIT License |
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Simple-MADRL-Chess
machin
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Best PyTorch RL library for doing research
Machin is really nice, it is very easy to use and to try different things, although it’s developed by one person and maybe not appropriately tested yet.
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Is there a consensus about RL frameworks?
I found this repo very helpful to get started: https://github.com/iffiX/machin
What are some alternatives?
warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
R-NaD - Experimentation with Regularized Nash Dynamics on a GPU accelerated game
Apache Impala - Apache Impala
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
PantheonRL - PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
tianshou - An elegant PyTorch deep reinforcement learning library.
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥