Update README.md

Author: ArzhelaR

README.md

@@ -13,3 +13,70 @@ block decomposition of polygons**" (see [arxiv article](https://arxiv.org/pdf/23
 and [presentation](http://tetrahedronvii.cimne.com/slides/Persson.pdf)).
 
 #### See the documentation website for more details: https://lihpc-computational-geometry.github.io/tune/
+
+## Installation
+The project can be cloned from github
+
+## Usage 
+The project can be used to train a reinforcement learning agent on **triangular meshes** or **quadrangular meshes**.
+
+---
+
+### Triangular Meshes
+
+For training on triangular meshes, you can use an agent with all three actions: **flip**, **split**, and **collapse**. Two training models are available:
+
+1. **Custom PPO Model** (`tune/model_RL/PPO_model`)
+2. **PPO from Stable Baselines 3 (SB3)**
+
+#### 🚀 Starting Training
+
+##### 1. Using `tune/model_RL/PPO_model`
+
+- Configure the model and environment parameters in:  
+  `tune/training/train.py`
+
+- Then run the following command from the `tune/` directory:
+  ```bash
+  python main.py
+  ```
+
+
+##### 2. Using PPO from Stable Baselines 3 (SB3)
+
+- Configure the model and environment parameters in:  
+    - `tune/environment/environment_config.json`
+    - `tune/model_RL/parameters/PPO_config.json`
+
+- Then run the training script in pycharm `tune/training/train_trimesh_SB3.py`
+
+###### Flip-Only Training (SB3 PPO)
+
+To train an agent using only the flip action with SB3 PPO, run the training script in pycharm `tune/training/train_trimesh_flip_SB3.py`
+
+---
+
+### Quadrangular Meshes
+
+For training on quadrangular meshes, you can use an agent with all four actions: **flip clockwise**, **flip counterclockwise**, **split**, and **collapse**. Two training models are available:
+
+1. **Custom PPO Model** (`tune/model_RL/PPO_model_pers`)
+2. **PPO from Stable Baselines 3 (SB3)**
+
+#### 🚀 Starting Training
+
+##### 1. Configure the model and environment parameters in :
+  - `tune/environment/environment_config.json`
+  - `tune/model_RL/parameters/PPO_config.json`
+  
+##### 2. Using `tune/model_RL/PPO_model_pers`
+Run the following command from the `tune/` directory:
+  ```bash
+  python -m /training/train_quadmesh
+  ```
+
+##### 3. Using PPO from Stable Baselines 3 (SB3)
+Run the training script in pycharm `tune/training/train_quadmesh_SB3.py`
+
+
+