CARL

CARL (context adaptive RL) provides highly configurable contextual extensions to several well-known RL environments. It's designed to test your agent's generalization capabilities in all scenarios where intra-task generalization is important.

Benchmarks include:

• OpenAI gym classic control suite extended with several physics context features like gravity or friction

• OpenAI gym Box2D BipedalWalker, LunarLander and CarRacing, each with their own modification possibilities like new vehicles to race

• All Brax locomotion environments with exposed internal features like joint strength or torso mass

• Super Mario (TOAD-GAN), a procedurally generated jump'n'run game with control over level similarity

• RNADesign, an environment for RNA design given structure constraints with structures from different datasets to choose from

Description from: CARL

Image source: https://github.com/automl/CARL