There are many different types of reinforcement learning algorithms, but two main categories are “model-based” and “model-free” RL. They are both inspired by our understanding of learning ...

SEED RL is built atop of the TensorFlow 2.0 framework and works by leveraging a combination of graphics processing units and tensor processing units to centralize model inference.

Google's Model Search system addresses this problem using a two-phased approach that resembles RL's "exploration vs. exploitation" tradeoff. In the exploration phase, a greedy search algorithm is ...