Monte Carlo Tree Search Reading List

Curated by Mouhssine Rifaki | Stanford Electrical Engineering | Last updated April 2026

The evolution of MCTS from its origins in Go to modern planning and environment design.

1. Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search
   Coulom. CG 2006.
2. Bandit Based Monte-Carlo Planning
   Kocsis and Szepesvari. ECML 2006.
3. Mastering the Game of Go with Deep Neural Networks and Tree Search
   Silver et al.. Nature 2016.
4. Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
   Silver et al.. Science 2018.
5. Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
   Schrittwieser et al.. Nature 2020.
6. Learning and Planning in Complex Action Spaces
   Danihelka et al.. ICLR 2022.
7. Monte-Carlo Tree Search as Regularized Policy Optimization
   Grill et al.. ICML 2020.
8. Thinking Fast and Slow with Deep Learning and Tree Search
   Anthony, Tian, Barber. NeurIPS 2017.
9. Learning to Search with MCTSnets
   Guez et al.. NeurIPS 2018.