From 9ca076b7e70c31b04d3fa463d944f46ecd1e3121 Mon Sep 17 00:00:00 2001 From: Mark Stephenson Date: Wed, 29 May 2024 22:45:48 -0700 Subject: [PATCH] f --- README.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index b768cd0e..5c3a5c55 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,11 @@ + + # BSK-RL: Environments and Algorithms for Spacecraft Planning and Scheduling + [BSK-RL](https://avslab.github.io/bsk_rl/) ([Basilisk](https://hanspeterschaub.info/basilisk) + [Reinforcement Learning](https://en.wikipedia.org/wiki/Reinforcement_learning)) is a Python package for constructing [Gymnasium](https://gymnasium.farama.org/index.html) environments for spacecraft tasking problems. It is built on top of [Basilisk](https://hanspeterschaub.info/basilisk), a modular and fast spacecraft simulation framework, making the simulation environments high-fidelity and computationally efficient. BSK-RL also includes a collection of agents, training scripts, and examples for working with these environments. + BSK-RL is developed by the [Autonomous Vehicle Systems (AVS) Lab](https://hanspeterschaub.info/AVSlab.html) at the University of Colorado Boulder. ## Usage -Installation instructions, examples, and documentation can be found on the [BSK-RL website](https://avslab.github.io/bsk_rl/) (under construction). +Installation instructions, examples, and documentation can be found on the [BSK-RL website](https://avslab.github.io/bsk_rl/).