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Monte Carlo tree search
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A heuristic search algorithm used in decision processes, particularly in games, that balances exploration and exploitation using random sampling.
Technical Definition
A heuristic search algorithm used in decision processes, particularly in games, that balances exploration and exploitation using random sampling.
How it works
Monte Carlo Tree Search (MCTS) is a powerful algorithm for finding optimal decisions in complex domains, often used in games like Go. It works by building a search tree, using random sampling (Monte Carlo simulations) to estimate the value of different moves. This allows it to explore promising branches while also balancing exploration with exploitation.
Related Concepts
- Reinforcement Learning — A paradigm where an agent learns to make decisions by receiving rewards or penalties from its environment through trial and error.
- Search algorithm — A process for finding information or solutions within data or a problem space.