Reinforcement Learning with Prediction-Based Rewards (via) Fascinating result: by teaching a reinforcement learning agent that plays video games to optimize for “unfamiliar states”—states where it cannot predict what will happen next—the agent does a much better job of playing some games. “... for the first time exceeds average human performance on Montezuma’s Revenge. RND achieves state-of-the-art performance, periodically finds all 24 rooms and solves the first level without using demonstrations or having access to the underlying state of the game.”
Recent articles
- Highlights from my appearance on the Data Renegades podcast with CL Kao and Dori Wilson - 26th November 2025
- Claude Opus 4.5, and why evaluating new LLMs is increasingly difficult - 24th November 2025
- sqlite-utils 4.0a1 has several (minor) backwards incompatible changes - 24th November 2025