# TurboGP: A flexible and advanced python based GP library

arXiv: https://arxiv.org/abs/2309.00149 · HTML: https://mlsanity.com/paper/2309.00149/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 24 references that are in the map.
- First posted on arXiv 31 Aug 2023.

## Builds on (most cited first, 2 of 2)

- [Evolving Reinforcement Learning Algorithms](https://mlsanity.com/paper/2101.03958/) (2021)
- [TensorFlow Enabled Genetic Programming](https://mlsanity.com/paper/1708.03157/) (2017)

## Abstract (arXiv)

We introduce TurboGP, a Genetic Programming (GP) library fully written in Python and specifically designed for machine learning tasks. TurboGP implements modern features not available in other GP implementations, such as island and cellular population schemes, different types of genetic operations (migration, protected crossovers), online learning, among other features. TurboGP's most distinctive characteristic is its native support for different types of GP nodes to allow different abstraction levels, this makes TurboGP particularly useful for processing a wide variety of data sources.