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README.md

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 # BSK-RL: Environments and Algorithms for Spacecraft Planning and Scheduling
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 [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.
 
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 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/).