Augmented Random Search for Reinforcement Learning in Matlab
Updated 14 Nov 2021

Augmented Random Search For Reinforcement Learning in MATLAB

What is this?

An implementation of Augmented Random Search in Matlab. It supports Matlab environments compatible with the Matlab RL Toolbox. It also requires the Parallel computing toolbox.

Why should I use this?

ARS is a very simple, fast algorithm that can often outperform more complex state of the art reinforcement learning algorithms (Like PPO, SAC, TD3 etc.), especially when comparing to the official mathworks implementations (which in my experience are missing many of the performance tricks from more mature python implementations of these algorithms).

In addition MATLAB's JIT makes using ARS with simple MATLAB environments very fast, even more so when comparing to pure python implementations of say, a cartpole pendulum or similar. For most environments I've tested I see hundreds of thousands of steps per second.

How do I use this?

Just clone this repo anywhere on your computer, and add it to your MATLAB path. From there see the examples folder to get you started.

Here's a reward curve


Cite As

Sean Gillen (2024). ARS in MATLAB (, GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2021b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.