This project aims to develop an agent using reinforcement learning for the placement of network functions. The project consists of the following four main components:

1. VNF Placement: This folder contains the machine learning code for the reinforcement learning agent.

2. Multi-Cluster Kubernetes envrionnement: This folder contains the source code for the deployment of a cloud-native simulation platform composed of several Kubernetes clusters created on-demand.

3. Topology generator: This folder allows you to generate network topologies using GT-ITM.

To install the required dependencies for each of the components, please refer to the instructions in each folder's respective README.md file.

Each of the four components can be used independently, but they can also be combined to form a complete solution for network function placement using reinforcement learning.

Please refer to each folder's respective README.md file for detailed usage instructions.

We welcome contributions from the community. If you would like to contribute to this project, please open an issue or submit a pull request.