flâneur — a map of the web's best reading

Understanding RL Vision

distill.pub · 9,098 words · saved by 1 readers

With diverse environments, we can analyze, diagnose and edit deep reinforcement learning models using attribution.

Understanding RL Vision Distill Understanding RL Vision With diverse environments, we can analyze, diagnose and edit deep reinforcement learning models using attribution. Observation (video game still) Positive attribution (good news) Negative attribution (bad news) Attribution from a hidden layer to the value function, showing what features of the observation (left) are used to predict success (middle) and failure (right). Applying dimensionality reduction (NMF) yields features that detect various in-game objects. Coin Enemy Buzzsaw Authors Affiliations Jacob Hilton OpenAI Nick Cammarata Open

Explore this link on the map →

related reading