Monte Carlo Tree Search, MCTS
Version 1.0.0 · Updated 2026-07-28
CORE DEFINITION
Monte Carlo tree search (MCTS) is a heuristic search algorithm used for certain decision-making processes, most notably in games. A major example is computer Go programs; it is also used in other board games, real-time video games, and games with uncertainty.
SCAFFOLDING EFFECT
Reduce cognitive load
Monte Carlo tree search (MCTS) is a heuristic search algorithm used for certain decision-making processes, most notably in games. A major example is computer Go programs; it is also used in other board games, real-time video games, and games with uncertainty.
Anchor fast decisions
In large decision spaces, it balances exploration and exploitation using random simulation and tree search: iterating through four steps—selection, expansion, simulation, and backpropagation—to gradually focus on high-value paths.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
account_treeGenealogyexpand_more
menu_bookReferencesexpand_more
Source support: Explicit
- zh.wikipedia.orghttps://zh.wikipedia.org/wiki/%E8%92%99%E7%89%B9%E5%8D%A1%E6%B4%9B%E6%A0%91%E6%90%9C%E7%B4%A2verified
PRIVATE NOTES · Only visible to you
SAVED Q&A
ENTRY Q&A · Private saving available
Ask with a clear boundary
thinkingmodels answers from published entry context only.
Your question is sent to thinkingmodels. The answer uses public entry context only.
RELATED MODELS