#neuroevolution

EvoJAX is a toolkit designed for hardware-accelerated neuroevolution, utilizing multi-TPU/GPU setups for parallel processing. Based on the JAX library, it facilitates quick experiments across various learning tasks by using NumPy for just-in-time compilation, aiming to improve computational efficiency. The toolkit supports customization via its trainer and simulation manager components and encourages community contributions in advanced algorithms and task development.

Evosax enables efficient neuroevolution through JAX and XLA, incorporating both classic (CMA-ES) and modern (OpenAI-ES) strategies. Utilize auto-vectorization and parallelization for optimal performance on accelerators, simplifying cycle management. Evosax provides robust implementations for scalable evolutionary computations, ideal for high-throughput needs without async complexity.