# Custom Algorithms and Policies

Our benchmark is not constrained to the presented algorithms. You can always add in your new algorithm. In this repo, we have also included a lifelong learning algorithm [AGEM]().

To see an example of your own algorithm or policy architecture, please refer to the following notebook as a step-by-step example:
```
jupyter notebook notebooks/quick_guide_algo.ipynb
```