# SafePILCO: a software tool for safe and data-efficient policy synthesis

arXiv: https://arxiv.org/abs/2008.03273 · HTML: https://mlsanity.com/paper/2008.03273/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Aug 2020.

## Built on by (most cited first, 3 of 3)

- [Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation](https://mlsanity.com/paper/2202.06558/) (2022)
- [Effects of Safety State Augmentation on Safe Exploration](https://mlsanity.com/paper/2206.02675/) (2022)
- [FORESEE: Prediction with Expansion-Compression Unscented Transform for Online Policy Optimization](https://mlsanity.com/paper/2209.12644/) (2022)

## Abstract (arXiv)

SafePILCO is a software tool for safe and data-efficient policy search with reinforcement learning. It extends the known PILCO algorithm, originally written in MATLAB, to support safe learning. We provide a Python implementation and leverage existing libraries that allow the codebase to remain short and modular, which is appropriate for wider use by the verification, reinforcement learning, and control communities.