Google releases open source reinforcement learning framework for training AI models

The trouble is, reinforcement learning frameworks take time to master a goal, tend to be inflexible, and aren't always stable. That's why Google is proposing an alternative: an open source reinforcement framework based on TensorFlow, its machine learning library. "Inspired by one of the main components in reward-motivated behavior in the brain and reflecting the strong historical connection between neuroscience and reinforcement learning research, this platform aims to enable the kind of speculative research that can drive radical discoveries," Pablo Samuel Castro and Marc G. Bellemare, researchers on the Google Brain Team, wrote in a blog post. "This release also includes a set of colabs that clarify how to use our framework." They and the Google Brain team developed the reinforcement framework with three tenets in mind: flexibility, stability, and reproducibility.