# LCPPO: An Efficient Multi-agent Reinforcement Learning Algorithm on Complex Railway Network

> This is the code for LCPPO.



## Install requirements

```bash
conda create -n flatland python=3.8
BASE_DIR=flatland-marllib
cd $BASE_DIR/marllib/envs/flatland_env/flatland-rl
pip install -e .
cd $BASE_DIR/marllib/envs/flatland_env//flat_cutils
pip install -e . 
cd $BASE_DIR//marllib/
pip install -r requirements.txt
```



## Train agents

```bash
cd experiments
bash train.sh
```



## Test agents

```bash
cd experiments
bash test.sh
```

