Researchers at the University of Oxford Introduce Craftax: A Machine Learning Benchmark for Open-Ended Reinforcement Learning

Univ. of Oxford & Univ. College London present Craftax, a JAX-based RL benchmark outperforming others in speed. It offers Craftax-Classic, solvable by a basic PPO agent in 51 mins, encouraging higher timesteps gain. Despite disappointing existing approaches, Craftax aims to facilitate RL research with limited resources. Craftax-Classic serves as an entry point for Crafter users.

 Researchers at the University of Oxford Introduce Craftax: A Machine Learning Benchmark for Open-Ended Reinforcement Learning

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Introducing Craftax: A Machine Learning Benchmark for Open-Ended Reinforcement Learning

Building and using benchmarks is crucial for advancing in RL algorithms. For value-based deep RL algorithms, benchmarks like Arcade Learning Environment, Mujoco for continuous control, and StarCraft Multi-Agent Challenge for multi-agent RL are available. Additionally, tools like MiniHack, Crafter, MALMO, and The NetHack Learning Environment have been created to demonstrate open-ended dynamics.

However, these benchmarks often have lengthy runtimes, making them impractical for use with current methods. On the other hand, JAX has seen a rise in RL environments due to faster running times, thanks to effective parallelization and compilation.

The Craftax Benchmark

Addressing the need for faster benchmarks, researchers from the University of Oxford and University College London have developed Craftax, an environment based on JAX that runs significantly quicker than similar benchmarks. For example, Craftax-Classic, a JAX reimplementation of Crafter, outperforms the original version by 250.

The study demonstrates that a basic PPO agent can solve Craftax-Classic in 51 minutes, providing easy access to significantly more timesteps. Additionally, a more challenging setting, Craftax, is introduced to offer a more appealing challenge with mechanics borrowed from the Roguelike genre.

Furthermore, the researchers provide Craftax variants that use symbolic observations as well as pixel-based observations, catering to different computational resource constraints.

The team hopes that Craftax-Classic will offer a smooth introduction to Craftax for individuals familiar with the Crafter standard.

Check out the Paper, Github, and Project.

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