Co-authored MuZero: planning with a learned model across games and Atari.
Researcher Profile
Edward Lockhart
Planning with learned dynamics (MuZero)
Researcher at Google DeepMind
Co-authored MuZero: planning with a learned model across games and Atari.
Organizations
Labs
Topics
About This Page
This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.
Last updated
March 20, 2026
Official And External Links
Known For
The ideas, systems, and research directions that make this person worth knowing.
01
Planning with learned dynamics (MuZero)
02
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
03
DeepMind
04
Model-based RL
05
Model-Based RL
06
Planning
Start Here
Canonical papers, project pages, or repositories that anchor this profile.
Signature Works
Additional papers, projects, or repositories that help flesh out the profile.
Supporting Sources
Additional links that help verify and flesh out this profile.
Related Researchers
People worth exploring next because they share topics, labs, or source material with this profile.
A central figure in modern reinforcement learning whose work turned deep RL from an exciting idea into a line of systems that repeatedly reset expectations.
Co-authored AlphaZero: a canonical reference for self-play + search in RL.
Co-authored AlphaZero: a canonical reference for self-play + search in RL.
Co-authored AlphaZero: a canonical reference for self-play + search in RL.
Co-authored AlphaZero: a canonical reference for self-play + search in RL.