AI engineering glossary · Reinforcement learning
What is MCTS (Monte Carlo tree search)?
Monte Carlo tree search (also called MCTS): A planning algorithm that builds a search tree by repeatedly selecting promising moves, expanding a new position, simulating to the end, and backing the result up the tree. It balances trying and exploiting with a bandit rule and works without a full evaluation function.
Monte Carlo tree search: an example
A Go program runs 800 simulations from the current position before choosing its move.
Related terms
More Reinforcement learning terms
- Multi-agent reinforcement learning
- Multi-armed bandit
- MuZero
- n-step return
- Nash equilibrium
- Natural policy gradient
- Noisy networks
- Off-policy
Where you learn it
Monte Carlo tree search is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.