Gym Retro

📰 OpenAI News

OpenAI releases Gym Retro, a platform for reinforcement learning research on over 1,000 games

intermediate Published 25 May 2018
Action Steps
  1. Explore the Gym Retro platform and its features
  2. Use the provided tool to add new games to the platform
  3. Train and test reinforcement learning models on the available games
  4. Analyze and compare results across different games and emulators
Who Needs to Know This

Researchers and engineers on AI teams can benefit from this platform to train and test reinforcement learning models, while data scientists can explore new possibilities for game-based research

Key Insight

💡 Gym Retro provides a large-scale platform for reinforcement learning research on a variety of games

Share This
🚀 Gym Retro released with 1,000+ games for reinforcement learning research!

Key Takeaways

OpenAI releases Gym Retro, a platform for reinforcement learning research on over 1,000 games

Full Article

We’re releasing the full version of Gym Retro, a platform for reinforcement learning research on games. This brings our publicly-released game count from around 70 Atari games and 30 Sega games to over 1,000 games across a variety of backing emulators. We’re also releasing the tool we use to add new games to the platform.
Read full article → ← Back to Reads

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