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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.
| Date | Stars |
|---|---|
| 2026-07-31 | 1389 |
| 2026-08-04 | 1389 |
| 2026-08-06 | 1389 |
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Momentum
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growth rate 0.00%/day
# Overview
DI-star: A large-scale game AI distributed training platform specially developed for the StarCraft II. We've already trained grand-master AI！This project contains:
- [x] Play demo and test code (try and play with our agent!)
- [x] First version of pre-trained SL and RL agent (only Zerg vs Zerg)
- [x] Training code of Supervised Learning and Reinforcement Learning *(updated by 2022-01-31)*
- [x] Training baseline with limited resource(one PC) and training guidance [here](docs/guidance_to_small_scale_training.md) *(New! updated 2022-04-24)*
- [x] Agents fought with [Harstem (YouTube)](https://www.youtube.com/watch?v=fvQF-24IpXs&t=813s) *(updated by 2022-04-01)*
- [ ] More stronger pre-trained RL agents *(WIP)*
## Usage
[Testing software on Windows](docs/installation.md) | [对战软件下载](docs/安装教程.md)
Please star us (click  button in the top-right of this page) to help DI-star agents to grow up faster :)
### Installation
Environment requirement:
- Python: 3.6-3.8
#### 1.Install StarCraftII
- Download the retail version of StarCraftII: https://starcraft2.com
Note: There is no retail version on Linux, please follow the instruction [here](https://github.com/Blizzard/s2client-proto#downloads)
- Add SC2 installation path to environment variables ```SC2PATH``` (skip this if you use default installation path on MacOS or Windows, which is `C:\Program Files (x86)\StarCraft II` or `/Applications/StarCraft II`):
- On MacOS or Linux, input this in terminal:
```shell
export SC2PATH=<sc2/installation/path>
```
- On Windows:
1. Right-click the Computer icon and choose Properties, or in Windows Control Panel, choose System.
2. Choose Advanced system settings.
3. On the Advanced tab, click Environment Variables.
4. Click New to create a new environment variable, set ```SC2PATH``` as the sc2 installation location.
5. After creating or modifying the environment variable, click Apply and then OK to have the change take effect.
#### 2.Install distar:
```bash
git clone https://github.com/opendilab/DI-star.git
cd DI-star
pip install -e .
```
#### 3.Install pytorch:
Pytorch Version 1.7.1 and CUDA is recommended, Follow instructions from [pytorch official site](https://pytorch.org/get-started/previous-versions/)
**Note: GPU is neccessary for decent performance in realtime agent test, you can also use pytorch without cuda, but no performance guaranteed due to inference latency on cpu.
Make sure you set SC2 at lowest picture quality before testing.**
### Play with pretrained agent
#### 1. Download StarCraftII version 4.10.0
Double click the file [data/replays/replay_4.10.0.SC2Replay](data/replays/replay_4.10.0.SC2Replay), StarCraftII version 4.10.0 will be automatically downloaded.
Note: We trained our models with versions from 4.8.2 to 4.9.3. Patch 5.0.9 has came out in March 15, 2022, Some changes have huge impact on performance, so we fix our version at 4.10.0 in evaluation.
#### 2. Download models:
```bash
python -m distar.bin.download_model --name rl_model
```
Note: Specify `rl_model` or `sl_model` after `--name` to download reinforcement learning model or supervised model.
Model list:
- `sl_model`: training with human replays, skill is equal to diamond players.
- `rl_model`: used as default, training with reinforcement learning, skill is equal to master or grandmaster.
- `Abathur`: one of reinforcement learning models, likes playing mutalisk.
- `Brakk`: one of reinforcement learning models, likes lingbane rush.
- `Dehaka`: one of reinforcement learning models, likes playing roach ravager.
- `Zagara`: one of reinforcement learning models, likes roach rush.
#### 3. Agent test
With the given model, we provide multiple tests with our agent.
##### Play against Agent
```bash
python -m distar.bin.play
```
It runs 2 StarCraftII instances. First one is controlleExcerpt of 8,558 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c7704e4aead87415, topic:deep-learning, desc:distributed training
matched fp:c7704e4aead87415, topic:deep-reinforcement-learning
