README.md

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---

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Updated on 2021.12.03 DI-engine-v0.2.2 (beta)


## Introduction to DI-engine (beta)
[DI-engine doc](https://di-engine-docs.readthedocs.io/en/latest/) | [中文文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/)

**DI-engine** is a generalized decision intelligence engine. It supports **various [deep reinforcement learning](https://di-engine-docs.readthedocs.io/en/latest/intro_rl/basic.html) algorithms** ([link](https://github.com/opendilab/DI-engine#algorithm-versatility)):

- Most basic DRL algorithms, such as DQN, PPO, SAC, R2D2
- Multi-agent RL algorithms like QMIX, MAPPO
- Imitation learning algorithms (BC/IRL/GAIL) , such as GAIL, SQIL, Guided Cost Learning
- Exploration algorithms like HER, RND, ICM
- Offline RL algorithms: CQL, TD3BC
- Model-based RL algorithms: MBPO

**DI-engine** aims to **standardize different RL enviroments and applications**. Various training pipelines and customized decision AI applications are also supported. 

- Traditional academic environments
  - [DI-zoo](https://github.com/opendilab/DI-engine#environment-versatility)
- Real world decision AI applications
  - [DI-star](https://github.com/opendilab/DI-star): Decision AI in StarCraftII
  - [DI-drive](https://github.com/opendilab/DI-drive): Auto-driving platform
  - [GoBigger](https://github.com/opendilab/GoBigger): Multi-Agent Decision Intelligence Environment
  - [DI-smartcross](https://github.com/opendilab/DI-smartcross): Decision AI in Traffic Light Control
- General nested data lib
  - [treevalue](https://github.com/opendilab/treevalue): Tree-nested data structure
  - [DI-treetensor](https://github.com/opendilab/DI-treetensor): Tree-nested PyTorch tensor Lib
- Docs and Tutorials
  - [DI-engine-docs](https://github.com/opendilab/DI-engine-docs)
  - [awesome-model-based-RL](https://github.com/opendilab/awesome-model-based-RL): A curated list of awesome Model-Based RL resources 

**DI-engine** also has some **system optimization and design** for efficient and robust large-scale RL training:

- [DI-orchestrator](https://github.com/opendilab/DI-orchestrator): RL Kubernetes Custom Resource and Operator Lib
- [DI-hpc](https://github.com/opendilab/DI-hpc): RL HPC OP Lib
- [DI-store](https://github.com/opendilab/DI-store): RL Object Store

Have fun with exploration and exploitation.

## Installation

You can simply install DI-engine from PyPI with the following command:
```bash
pip install DI-engine
```

If you use Anaconda or Miniconda, you can install DI-engine from conda-forge through the following command:
```bash
conda install -c opendilab di-engine
```

For more information about installation, you can refer to [installation](https://di-engine-docs.readthedocs.io/en/latest/installation/index.html).

And our dockerhub repo can be found [here](https://hub.docker.com/repository/docker/opendilab/ding)，we prepare `base image` and `env image` with common RL environments.

- base: opendilab/ding:nightly
- atari: opendilab/ding:nightly-atari
- mujoco: opendilab/ding:nightly-mujoco
- smac: opendilab/ding:nightly-smac

The detailed documentation are hosted on [doc](https://di-engine-docs.readthedocs.io/en/latest/) | [中文文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/).

## Quick Start

[3 Minutes Kickoff](https://di-engine-docs.readthedocs.io/en/latest/quick_start/index.html)

[3 Minutes Kickoff (colab)](https://colab.research.google.com/drive/1J29voOD2v9_FXjW-EyTVfRxY_Op_ygef#scrollTo=MIaKQqaZCpGz)

[3 分钟上手中文版 (kaggle)](https://www.kaggle.com/fallinx/di-engine/)

[How to migrate a new **RL Env**](https://di-engine-docs.readthedocs.io/en/latest/best_practice/ding_env.html) | [如何迁移一个新的**强化学习环境**](https://di-engine-docs.readthedocs.io/zh_CN/latest/best_practice/ding_env_zh.html)

**Bonus: Train RL agent in one line code:**

```bash
ding -m serial -e cartpole -p dqn -s 0
```

## Supporters

### &#8627; Stargazers

[![Stargazers repo roster for @opendilab/DI-engine](https://reporoster.com/stars/opendilab/DI-engine)](https://github.com/opendilab/DI-engine/stargazers)

### &#8627; Forkers

[![Forkers repo roster for @opendilab/DI-engine](https://reporoster.com/forks/opendilab/DI-engine)](https://github.com/opendilab/DI-engine/network/members)

## Feature

### Algorithm Versatility

|  No  |                          Algorithm                           |                            Label                             |                        Doc and Implementation                        |                        Runnable Demo                         |
| :--: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
|  1   |         [DQN](https://storage.googleapis.com/deepmind-media/dqn/DQNNaturePaper.pdf) | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [DQN doc](https://di-engine-docs.readthedocs.io/en/latest/hands_on/dqn.html)<br>[DQN中文文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/hands_on/dqn_zh.html)<br>[policy/dqn](https://github.com/opendilab/DI-engine/blob/main/ding/policy/dqn.py) | python3 -u cartpole_dqn_main.py / ding -m serial -c cartpole_dqn_config.py -s 0 |
|  2   |         [C51](https://arxiv.org/pdf/1707.06887.pdf)          | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/c51](https://github.com/opendilab/DI-engine/blob/main/ding/policy/c51.py) |        ding -m serial -c cartpole_c51_config.py -s 0         |
|  3   |         [QRDQN](https://arxiv.org/pdf/1710.10044.pdf)        | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/qrdqn](https://github.com/opendilab/DI-engine/blob/main/ding/policy/qrdqn.py) |       ding -m serial -c cartpole_qrdqn_config.py -s 0        |
|  4   |         [IQN](https://arxiv.org/pdf/1806.06923.pdf)          | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/iqn](https://github.com/opendilab/DI-engine/blob/main/ding/policy/iqn.py) |        ding -m serial -c cartpole_iqn_config.py -s 0         |
|  5   |         [Rainbow](https://arxiv.org/pdf/1710.02298.pdf)          | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/rainbow](https://github.com/opendilab/DI-engine/blob/main/ding/policy/rainbow.py) |      ding -m serial -c cartpole_rainbow_config.py -s 0       |
|  6   |         [SQL](https://arxiv.org/pdf/1702.08165.pdf)          | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)![continuous](https://img.shields.io/badge/-continous-green) | [policy/sql](https://github.com/opendilab/DI-engine/blob/main/ding/policy/sql.py) |        ding -m serial -c cartpole_sql_config.py -s 0         |
|  7   |         [R2D2](https://openreview.net/forum?id=r1lyTjAqYX)      | ![dist](https://img.shields.io/badge/-distributed-blue)![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/r2d2](https://github.com/opendilab/DI-engine/blob/main/ding/policy/r2d2.py) |        ding -m serial -c cartpole_r2d2_config.py -s 0        |
|  8   |         [A2C](https://arxiv.org/pdf/1602.01783.pdf)            | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/a2c](https://github.com/opendilab/DI-engine/blob/main/ding/policy/a2c.py) |        ding -m serial -c cartpole_a2c_config.py -s 0         |
|  9   |         [PPO](https://arxiv.org/abs/1707.06347)/[MAPPO](https://arxiv.org/pdf/2103.01955.pdf)         | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)![continuous](https://img.shields.io/badge/-continous-green)![MARL](https://img.shields.io/badge/-MARL-yellow) | [policy/ppo](https://github.com/opendilab/DI-engine/blob/main/ding/policy/ppo.py) | python3 -u cartpole_ppo_main.py / ding -m serial_onpolicy -c cartpole_ppo_config.py -s 0 |
|  10  |         [PPG](https://arxiv.org/pdf/2009.04416.pdf)          | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/ppg](https://github.com/opendilab/DI-engine/blob/main/ding/policy/ppg.py) |               python3 -u cartpole_ppg_main.py                |
|  11  |         [ACER](https://arxiv.org/pdf/1611.01224.pdf)         | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)![continuous](https://img.shields.io/badge/-continous-green) | [policy/acer](https://github.com/opendilab/DI-engine/blob/main/ding/policy/acer.py) |        ding -m serial -c cartpole_acer_config.py -s 0        |
|  12  |          [IMPALA](https://arxiv.org/abs/1802.01561)          | ![dist](https://img.shields.io/badge/-distributed-blue)![discrete](https://img.shields.io/badge/-discrete-brightgreen) | [policy/impala](https://github.com/opendilab/DI-engine/blob/main/ding/policy/impala.py) |       ding -m serial -c cartpole_impala_config.py -s 0       |
|  13  |         [DDPG](https://arxiv.org/pdf/1509.02971.pdf)/[PADDPG](https://arxiv.org/pdf/1511.04143.pdf)         | ![continuous](https://img.shields.io/badge/-continous-green)![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) | [policy/ddpg](https://github.com/opendilab/DI-engine/blob/main/ding/policy/ddpg.py) |        ding -m serial -c pendulum_ddpg_config.py -s 0        |
|  14  |         [TD3](https://arxiv.org/pdf/1802.09477.pdf)          | ![continuous](https://img.shields.io/badge/-continous-green)![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) | [policy/td3](https://github.com/opendilab/DI-engine/blob/main/ding/policy/td3.py) | python3 -u pendulum_td3_main.py / ding -m serial -c pendulum_td3_config.py -s 0 |
| 15 | [D4PG](https://arxiv.org/pdf/1804.08617.pdf) | ![continuous](https://img.shields.io/badge/-continous-green) | [policy/d4pg](https://github.com/opendilab/DI-engine/blob/main/ding/policy/d4pg.py) | python3 -u pendulum_d4pg_config.py |
|  16  |           [SAC](https://arxiv.org/abs/1801.01290)            | ![continuous](https://img.shields.io/badge/-continous-green) | [policy/sac](https://github.com/opendilab/DI-engine/blob/main/ding/policy/sac.py) |        ding -m serial -c pendulum_sac_config.py -s 0         |
| 17 | [PDQN](https://arxiv.org/pdf/1810.06394.pdf) | ![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) | [policy/pdqn](https://github.com/opendilab/DI-engine/blob/main/ding/policy/pdqn.py) | ding -m serial -c gym_hybrid_pdqn_config.py -s 0 |
| 18 | [MPDQN](https://arxiv.org/pdf/1905.04388.pdf) | ![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) | [policy/pdqn](https://github.com/opendilab/DI-engine/blob/main/ding/policy/pdqn.py) | ding -m serial -c gym_hybrid_mpdqn_config.py -s 0 |
|  19  |           [QMIX](https://arxiv.org/pdf/1803.11485.pdf)           |      ![MARL](https://img.shields.io/badge/-MARL-yellow)      | [policy/qmix](https://github.com/opendilab/DI-engine/blob/main/ding/policy/qmix.py) |       ding -m serial -c smac_3s5z_qmix_config.py -s 0        |
|  20  |         [COMA](https://arxiv.org/pdf/1705.08926.pdf)         |      ![MARL](https://img.shields.io/badge/-MARL-yellow)      | [policy/coma](https://github.com/opendilab/DI-engine/blob/main/ding/policy/coma.py) |       ding -m serial -c smac_3s5z_coma_config.py -s 0        |
|  21  |          [QTran](https://arxiv.org/abs/1905.05408)           |      ![MARL](https://img.shields.io/badge/-MARL-yellow)      | [policy/qtran](https://github.com/opendilab/DI-engine/blob/main/ding/policy/qtran.py) |       ding -m serial -c smac_3s5z_qtran_config.py -s 0       |
|  22  |          [WQMIX](https://arxiv.org/abs/2006.10800)           |      ![MARL](https://img.shields.io/badge/-MARL-yellow)      | [policy/wqmix](https://github.com/opendilab/DI-engine/blob/main/ding/policy/wqmix.py) |       ding -m serial -c smac_3s5z_wqmix_config.py -s 0       |
|  23  |        [CollaQ](https://arxiv.org/pdf/2010.08531.pdf)        |      ![MARL](https://img.shields.io/badge/-MARL-yellow)      | [policy/collaq](https://github.com/opendilab/DI-engine/blob/main/ding/policy/collaq.py) |      ding -m serial -c smac_3s5z_collaq_config.py -s 0       |
|  24  |           [GAIL](https://arxiv.org/pdf/1606.03476.pdf)           |        ![IL](https://img.shields.io/badge/-IL-purple)        | [reward_model/gail](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/gail_irl_model.py) |  ding -m serial_gail -c cartpole_dqn_gail_config.py -s 0  |
|  25  |         [SQIL](https://arxiv.org/pdf/1905.11108.pdf)         |        ![IL](https://img.shields.io/badge/-IL-purple)        | [entry/sqil](https://github.com/opendilab/DI-engine/blob/main/ding/entry/serial_entry_sqil.py) |     ding -m serial_sqil -c cartpole_sqil_config.py -s 0      |
|  26  | [DQFD](https://arxiv.org/pdf/1704.03732.pdf) | ![IL](https://img.shields.io/badge/-IL-purple) | [policy/dqfd](https://github.com/opendilab/DI-engine/blob/main/ding/policy/dqfd.py) | ding -m serial_dqfd -c cartpole_dqfd_config.py -s 0 |
|  27  | [R2D3](https://arxiv.org/pdf/1909.01387.pdf) | ![IL](https://img.shields.io/badge/-IL-purple) | [R2D3中文文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/hands_on/r2d3_zh.html)<br>[policy/r2d3](https://github.com/opendilab/DI-engine/blob/main/ding/policy/r2d3.py) | python3 -u pong_r2d3_r2d2expert_config.py |
|  28  |     [Guided Cost Learning](https://arxiv.org/pdf/1603.00448.pdf)     |   ![IL](https://img.shields.io/badge/-IL-purple)             | [reward_model/guided_cost](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/guided_cost_reward_model.py) |                          python3 lunarlander_gcl_config.py   |
|  29  |         [TREX](https://arxiv.org/abs/1904.06387)          |   ![IL](https://img.shields.io/badge/-IL-purple)             | [reward_model/trex](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/trex_reward_model.py) |                          python3 mujoco_trex_main.py   |
|  30  |           [HER](https://arxiv.org/pdf/1707.01495.pdf)            |   ![exp](https://img.shields.io/badge/-exploration-orange)   | [reward_model/her](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/her_reward_model.py) |                python3 -u bitflip_her_dqn.py                 |
|  31  |           [RND](https://arxiv.org/abs/1810.12894)            |   ![exp](https://img.shields.io/badge/-exploration-orange)   | [reward_model/rnd](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/rnd_reward_model.py) |             python3 -u cartpole_ppo_rnd_main.py              |
|  32  |           [ICM](https://arxiv.org/pdf/1705.05363.pdf)            |   ![exp](https://img.shields.io/badge/-exploration-orange)   | [ICM中文文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/hands_on/icm_zh.html)<br>[reward_model/icm](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/icm_reward_model.py) |             python3 -u cartpole_ppo_icm_config.py              |
|  33  |         [CQL](https://arxiv.org/pdf/2006.04779.pdf)          | ![offline](https://img.shields.io/badge/-offlineRL-darkblue) | [policy/cql](https://github.com/opendilab/DI-engine/blob/main/ding/policy/cql.py) |                 python3 -u d4rl_cql_main.py                  |
|  34  |         [TD3BC](https://arxiv.org/pdf/2106.06860.pdf)          | ![offline](https://img.shields.io/badge/-offlineRL-darkblue) | [policy/td3_bc](https://github.com/opendilab/DI-engine/blob/main/ding/policy/td3_bc.py) |                 python3 -u mujoco_td3_bc_main.py                  |
|  35  |         [MBPO](https://arxiv.org/pdf/1906.08253.pdf)         | ![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) | [model/template/model_based/mbpo](https://github.com/opendilab/DI-engine/blob/main/ding/model/template/model_based/mbpo.py) |        python3 -u sac_halfcheetah_mopo_default_config.py     |
|  36  |         [PER](https://arxiv.org/pdf/1511.05952.pdf)          |   ![other](https://img.shields.io/badge/-other-lightgrey)    | [worker/replay_buffer](https://github.com/opendilab/DI-engine/blob/main/ding/worker/replay_buffer/advanced_buffer.py) |                        `rainbow demo`                        |
|  37  |         [GAE](https://arxiv.org/pdf/1506.02438.pdf)          |   ![other](https://img.shields.io/badge/-other-lightgrey)    | [rl_utils/gae](https://github.com/opendilab/DI-engine/blob/main/ding/rl_utils/gae.py) |                          `ppo demo`                          |

![discrete](https://img.shields.io/badge/-discrete-brightgreen) means discrete action space, which is only label in normal DRL algorithms (1-18)

![continuous](https://img.shields.io/badge/-continous-green) means continuous action space, which is only label in normal DRL algorithms (1-18)

![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) means hybrid (discrete + continuous) action space (1-18)

![dist](https://img.shields.io/badge/-distributed-blue) means distributed training (collector-learner parallel) RL algorithm

![MARL](https://img.shields.io/badge/-MARL-yellow) means multi-agent RL algorithm

![exp](https://img.shields.io/badge/-exploration-orange) means RL algorithm which is related to exploration and sparse reward

![IL](https://img.shields.io/badge/-IL-purple) means Imitation Learning, including Behaviour Cloning, Inverse RL, Adversarial Structured IL

![offline](https://img.shields.io/badge/-offlineRL-darkblue) means offline RL algorithm

![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) means model-based RL algorithm

![other](https://img.shields.io/badge/-other-lightgrey) means other sub-direction algorithm, usually as plugin-in in the whole pipeline

P.S: The `.py` file in `Runnable Demo` can be found in `dizoo`


### Environment Versatility
|  No  |                Environment               |                 Label               |         Visualization            |                   Code and Doc Links                   |
| :--: | :--------------------------------------: | :---------------------------------: | :--------------------------------:|:---------------------------------------------------------: |
|  1   |       [atari](https://github.com/openai/gym/tree/master/gym/envs/atari)    | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)   | ![original](./dizoo/atari/atari.gif)     |        [code link](https://github.com/opendilab/DI-engine/tree/main/dizoo/atari/envs) <br>[env tutorial](https://di-engine-docs.readthedocs.io/en/latest/env_tutorial/atari.html)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/atari_zh.html)        |
|  2   |       [box2d/bipedalwalker](https://github.com/openai/gym/tree/master/gym/envs/box2d)    | ![continuous](https://img.shields.io/badge/-continous-green) | ![original](./dizoo/box2d/bipedalwalker/original.gif)        | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/box2d/bipedalwalker/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/bipedalwalker_zh.html) |
|  3   |       [box2d/lunarlander](https://github.com/openai/gym/tree/master/gym/envs/box2d)      | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)   | ![original](./dizoo/box2d/lunarlander/lunarlander.gif)   |  [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/box2d/lunarlander/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/lunarlander_zh.html)  |
|  4   |       [classic_control/cartpole](https://github.com/openai/gym/tree/master/gym/envs/classic_control)       | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)   | ![original](./dizoo/classic_control/cartpole/cartpole.gif)    | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/classic_control/cartpole/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/cartpole_zh.html) |
|  5   |       [classic_control/pendulum](https://github.com/openai/gym/tree/master/gym/envs/classic_control)       | ![continuous](https://img.shields.io/badge/-continous-green) | ![original](./dizoo/classic_control/pendulum/pendulum.gif)    | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/classic_control/pendulum/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/pendulum_zh.html) |
|  6   |       [competitive_rl](https://github.com/cuhkrlcourse/competitive-rl)       | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) ![selfplay](https://img.shields.io/badge/-selfplay-blue) | ![original](./dizoo/competitive_rl/competitive_rl.gif)   |  [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo.classic_control)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/competitive_rl_zh.html)  |
|  7   |       [gfootball](https://github.com/google-research/football)                        | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)![sparse](https://img.shields.io/badge/-sparse%20reward-orange)![selfplay](https://img.shields.io/badge/-selfplay-blue) | ![original](./dizoo/gfootball/gfootball.gif)      | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo.gfootball/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/gfootball_zh.html) |
|  8   |       [minigrid](https://github.com/maximecb/gym-minigrid)                         | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)![sparse](https://img.shields.io/badge/-sparse%20reward-orange) | ![original](./dizoo/minigrid/minigrid.gif)         | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/minigrid/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/minigrid_zh.html) |
|  9   |       [mujoco](https://github.com/openai/gym/tree/master/gym/envs/mujoco)       |  ![continuous](https://img.shields.io/badge/-continous-green)  | ![original](./dizoo/mujoco/mujoco.gif)                    | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/majoco/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/mujoco_zh.html) |
|  10   |       [multiagent_particle](https://github.com/openai/multiagent-particle-envs)         | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) ![marl](https://img.shields.io/badge/-MARL-yellow)  | ![original](./dizoo/multiagent_particle/multiagent_particle.gif)     |  [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/multiagent_particle/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/multiagent_particle_zh.html)  |
|  11   |       [overcooked](https://github.com/HumanCompatibleAI/overcooked-demo)     | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) ![marl](https://img.shields.io/badge/-MARL-yellow)  | ![original](./dizoo/overcooked/overcooked.gif)       |   [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/overcooded/envs)<br>[env tutorial](https://di-engine-docs.readthedocs.io/en/latest/env_tutorial/overcooked.html)   |
|  12  |       [procgen](https://github.com/openai/procgen)                          | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)   | ![original](./dizoo/procgen/coinrun/coinrun.gif) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/procgen)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/procgen_zh.html) |
|  13  |       [pybullet](https://github.com/benelot/pybullet-gym)    | ![continuous](https://img.shields.io/badge/-continous-green)  | ![original](./dizoo/pybullet/pybullet.gif)       | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/pybullet/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/pybullet_zh.html) |
|  14  |       [smac](https://github.com/oxwhirl/smac)     | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) ![marl](https://img.shields.io/badge/-MARL-yellow)![selfplay](https://img.shields.io/badge/-selfplay-blue)![sparse](https://img.shields.io/badge/-sparse%20reward-orange) | ![original](./dizoo/smac/smac.gif)       | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/smac/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/smac_zh.html) |
| 15 | [d4rl](https://github.com/rail-berkeley/d4rl) | ![offline](https://img.shields.io/badge/-offlineRL-darkblue) | ![ori](dizoo/d4rl/d4rl.gif) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/d4rl)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/d4rl_zh.html) |
|  16  |       league_demo                      | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) ![selfplay](https://img.shields.io/badge/-selfplay-blue) | ![original](./dizoo/league_demo/league_demo.png) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/league_demo/envs)                |
|  17  |       pomdp atari                    | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)   |  | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/pomdp/envs) |
|  18  |       [bsuite](https://github.com/deepmind/bsuite)                         | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) | ![original](./dizoo/bsuite/bsuite.png) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/bsuite/envs)<br>[env tutorial](https://di-engine-docs.readthedocs.io/en/latest/env_tutorial/bsuite.html) |
| 19 | [ImageNet](https://www.image-net.org/) | ![IL](https://img.shields.io/badge/-IL/SL-purple) | ![original](./dizoo/image_classification/imagenet.png) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/image_classification)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/image_cls_zh.html) |
| 20 | [slime_volleyball](https://github.com/hardmaru/slimevolleygym) | ![discrete](https://img.shields.io/badge/-discrete-brightgreen)![selfplay](https://img.shields.io/badge/-selfplay-blue) | ![ori](dizoo/slime_volley/slime_volley.gif) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/slime_volley)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/slime_volleyball_zh.html) |
| 21 | [gym_hybrid](https://github.com/thomashirtz/gym-hybrid) | ![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) | ![ori](dizoo/gym_hybrid/moving_v0.gif) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/gym_hybrid)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/gym_hybrid_zh.html) |
| 22 | [GoBigger](https://github.com/opendilab/GoBigger) | ![hybrid](https://img.shields.io/badge/-hybrid-darkgreen)![marl](https://img.shields.io/badge/-MARL-yellow)![selfplay](https://img.shields.io/badge/-selfplay-blue) | ![ori](./dizoo/gobigger_overview.gif) | [opendilab link](https://github.com/opendilab/GoBigger-Challenge-2021/tree/main/di_baseline)<br>[env tutorial](https://gobigger.readthedocs.io/en/latest/index.html)<br>[环境指南](https://gobigger.readthedocs.io/zh_CN/latest/) |
| 23 | [gym_soccer](https://github.com/openai/gym-soccer) | ![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) | ![ori](dizoo/gym_soccer/half_offensive.gif) | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/gym_soccer)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/gym_soccer_zh.html) |
| 24 |[multiagent_mujoco](https://github.com/schroederdewitt/multiagent_mujoco)       |  ![continuous](https://img.shields.io/badge/-continous-green) ![marl](https://img.shields.io/badge/-MARL-yellow) | ![original](./dizoo/mujoco/mujoco.gif)                    | [dizoo link](https://github.com/opendilab/DI-engine/tree/main/dizoo/multiagent_mujoco/envs)<br>[环境指南](https://di-engine-docs.readthedocs.io/zh_CN/latest/env_tutorial/mujoco_zh.html) |


![discrete](https://img.shields.io/badge/-discrete-brightgreen) means discrete action space

![continuous](https://img.shields.io/badge/-continous-green) means continuous action space

![hybrid](https://img.shields.io/badge/-hybrid-darkgreen) means hybrid (discrete + continuous) action space

![MARL](https://img.shields.io/badge/-MARL-yellow) means multi-agent RL environment

![sparse](https://img.shields.io/badge/-sparse%20reward-orange) means environment which is related to exploration and sparse reward

![offline](https://img.shields.io/badge/-offlineRL-darkblue) means offline RL environment

![IL](https://img.shields.io/badge/-IL/SL-purple) means Imitation Learning or Supervised Learning Dataset

![selfplay](https://img.shields.io/badge/-selfplay-blue) means environment that allows agent VS agent battle

P.S. some enviroments in Atari, such as **MontezumaRevenge**, are also sparse reward type

## Feedback and Contribution

- [File an issue](https://github.com/opendilab/DI-engine/issues/new/choose) on Github
- Open or participate in our [forum](https://github.com/opendilab/DI-engine/discussions)
- Discuss on DI-engine [slack communication channel](https://join.slack.com/t/opendilab/shared_invite/zt-v9tmv4fp-nUBAQEH1_Kuyu_q4plBssQ) or QQ group (700157520)
- Contributes to our future plan [Roadmap](https://github.com/opendilab/DI-engine/projects)

We appreciate all the feedbacks and contributions to improve DI-engine, both algorithms and system designs. And `CONTRIBUTING.md` offers some necessary information. 

## Citation
```latex
@misc{ding,
    title={{DI-engine: OpenDILab} Decision Intelligence Engine},
    author={DI-engine Contributors},
    publisher = {GitHub},
    howpublished = {\url{https://github.com/opendilab/DI-engine}},
    year={2021},
}
```

## License
DI-engine released under the Apache 2.0 license.