DiscoRL provides code for discovering and reproducing state-of-the-art reinforcement learning algorithms through meta-learning. The project centers on Disco103, a meta-learned update rule for RL training. It offers a JAX-based harness supporting both meta-evaluation of discovered update rules and meta-training new update rules from scratch, implemented using DeepMind’s Haiku and Flax frameworks.