Announced in 2016, Gym is an open-source Python library created to assist in the advancement of support learning algorithms. It aimed to standardize how environments are specified in AI research study, making published research more quickly reproducible [24] [144] while providing users with an easy interface for engaging with these environments. In 2022, brand-new developments of Gym have actually been relocated to the library Gymnasium. [145] [146]
Gym Retro

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

RoboSumo

Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack understanding of how to even walk, but are offered the goals of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adapt to changing conditions. When an agent is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, recommending it had found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could create an intelligence "arms race" that could increase an agent's capability to work even outside the context of the competitors. [148]
OpenAI 5

OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high skill level entirely through experimental algorithms. Before becoming a team of 5, the very first public demonstration took place at The International 2017, [forum.batman.gainedge.org](https://forum.batman.gainedge.org/index.php?action=profile