Gymnasium is an open-source Python library that defines the standard interface between reinforcement learning algorithms and environment implementations. Originally forked from OpenAI Gym, it provides a unified API for agent-environment interaction along with a collection of reference environments including classic control tasks, Box2D physics simulations, and Atari games. The library serves as the foundational tool for RL research, enabling reproducible benchmarking of learning algorithms across different agent implementations.