Announced in 2016, Gym is an open-source Python library designed to facilitate the development of reinforcement learning algorithms. It aimed to standardize how environments are specified in AI research study, making published research more easily reproducible [24] [144] while supplying users with a basic user interface for connecting with these environments. In 2022, brand-new developments of Gym have been transferred to the library Gymnasium. [145] [146]
Gym Retro

Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research study on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to fix single jobs. Gym Retro offers the ability to generalize between games with similar ideas however various appearances.

RoboSumo

Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have understanding of how to even walk, but are offered the objectives of finding out to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the agents learn how to adjust to altering conditions. When a representative is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might produce an intelligence "arms race" that might increase an agent's capability to work even outside the context of the competition. [148]
OpenAI 5

OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, [forum.batman.gainedge.org](https://forum.batman.gainedge.org/index.php?action=profile