Edit README.md

README.md

 
+# TD 1 Reinforcement Learning
+
+## Project Overview
+
+This project is part of the TD 1 Reinforcement Learning assignment. It includes implementations of reinforcement learning algorithms to solve the CartPole-v1 environment and train a robotic arm using Panda-gym.
+
+## Environment Setup
+
+### Python Virtual Environment
+
+To set up a Python virtual environment, use the following commands:
+
+python -m venv venv source venv/bin/activate # On macOS/Linux venv\Scripts\activate # On Windows
+
+bash
+Copy
+Edit
+
+### Required Libraries
+
+Install the necessary libraries with the following command:
+
+pip install gymnasium stable-baselines3 wandb panda-gym torch matplotlib
+
+csharp
+Copy
+Edit
+
+## Project Structure
+
+The project is organized as follows:
+
+. ├── README.md ├── a2c_sb3_cartpole.py ├── a2c_sb3_panda_reach.py ├── evaluate_reinforce_cartpole.py ├── reinforce_cartpole.py ├── reward_plot.png ├── script_hub.py ├── test.py ├── training_wandb.py ├── venv └── wandb
+
+markdown
+Copy
+Edit
+
+## Experiment Tracking
+
+### Weights & Biases
+
+- **CartPole Experiment:** The link to the Weights & Biases run is not available due to the unavailability of the sharing feature.  
+- **Panda Reach Experiment:** The link to the Weights & Biases run is not available due to the unavailability of the sharing feature.  
+
+## Trained Models
+
+### Hugging Face Hub
+
+- **CartPole Model:** Hugging Face Hub - CartPole Model  
+- **Panda Reach Model:** Hugging Face Hub - Panda Reach Model  
+
+## Usage
+
+### Running the CartPole Experiment
+
+To run the CartPole experiment, use the following command:
+
+python a2c_sb3_cartpole.py
+
+bash
+Copy
+Edit
+
+### Running the Panda Reach Experiment
+
+To run the Panda Reach experiment, use the following command:
+
+python a2c_sb3_panda_reach.py
+
+yaml
+Copy
+Edit
+
+### Evaluating the CartPole Model
+
+To evaluate the CartPole model, use the following command:
+
+python evaluate_reinforce_cartpole.py
+
+shell
+Copy
+Edit
+
+## Results
+
+### Reward Plot
+
+The reward plot is shown below:
+
+![Reward Plot](reward_plot.png)
+
+## License
+
+This project is licensed under the MIT License.
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