| openai/baselines |
14,949 |
|
37 |
2 |
over 2 years ago |
6 |
February 26, 2018 |
497 |
mit |
Python |
| OpenAI Baselines: high-quality implementations of reinforcement learning algorithms |
| thu-ml/tianshou |
7,125 |
|
0 |
10 |
about 2 years ago |
33 |
August 22, 2023 |
97 |
mit |
Python |
| An elegant PyTorch deep reinforcement learning library. |
| vwxyzjn/cleanrl |
3,947 |
|
0 |
0 |
about 2 years ago |
0 |
|
49 |
other |
Python |
| High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG) |
| sweetice/Deep-reinforcement-learning-with-pytorch |
2,741 |
|
0 |
0 |
about 3 years ago |
0 |
|
26 |
mit |
Python |
| PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and .... |
| seungeunrho/minimalRL |
2,417 |
|
0 |
0 |
almost 3 years ago |
0 |
|
21 |
mit |
Python |
| Implementations of basic RL algorithms with minimal lines of codes! (pytorch based) |
| marlbenchmark/on-policy |
990 |
|
0 |
0 |
over 2 years ago |
0 |
|
7 |
mit |
Python |
| This is the official implementation of Multi-Agent PPO (MAPPO). |
| lcswillems/rl-starter-files |
571 |
|
0 |
0 |
over 2 years ago |
0 |
|
9 |
mit |
Python |
| RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code |
| joschu/modular_rl |
523 |
|
0 |
0 |
almost 8 years ago |
0 |
|
10 |
mit |
Python |
| Implementation of TRPO and related algorithms |
| danaugrs/huskarl |
417 |
|
0 |
0 |
over 3 years ago |
3 |
May 03, 2019 |
14 |
mit |
Python |
| Deep Reinforcement Learning Framework + Algorithms |
| TianhongDai/reinforcement-learning-algorithms |
407 |
|
0 |
0 |
about 5 years ago |
0 |
|
4 |
|
Python |
| This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress) |
