Tom Silver

Physics engines do not need to be replaced by black-box neural networks—patching them with Bayesian-inferred code enables robots to actively discover missing physical mechanisms with drastically fewer real-world interactions.

Robots can now autonomously learn to avoid failures by transforming recovery experiences into abstract planning skills, achieving over 50% better performance on unseen tasks.