PaperNova
Reinforcement Learning
2016
ADVANCED

Mastering the Game of Go with Deep Neural Networks and Tree Search

David Silver, Aja Huang, Chris J. Maddison, et al. · 2016

AlphaGo. Combines deep policy/value networks with Monte Carlo tree search to beat the world champion — a landmark demonstration of RL at scale.

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What you'll get

  • Outline: a plain-English breakdown of the paper's core idea, prerequisites, and the concepts you'll need to implement it.
  • Exercises: five to ten hands-on tasks, each with a concept card, a prompt, a starter code stub, and a collapsible reference solution.
  • Runnable notebook: a single .ipynb you can download and open in Jupyter or VS Code to work through every exercise.
  • Extensions: suggested follow-up experiments so you don't stop at a faithful reimplementation.