OpenAI Gym (2016)

OpenAI Gym is a toolkit and collection of environments for developing and comparing reinforcement-learning algorithms. The 2016 paper presents a common interface across tasks including Atari games, board games, 2D and 3D physics simulations, and robotics. Its central contribution is infrastructure and standardization: researchers can train agents against comparable environments, reuse evaluation code, and report results within a shared ecosystem. The paper is historically important for making reinforcement-learning experimentation more accessible and reproducible, although the original project and benchmark conventions have since evolved.