Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX

Mahjax is a new fully vectorized Riichi Mahjong environment implemented in JAX, designed to enable large-scale rollout parallelization on GPUs for reinforcement learning research. It facilitates tabula rasa learning and includes a high-quality visualization tool for debugging trained agents.