Monte Carlo Tree Search (MCTS)¶
Monte Carlo Tree Search is a strategy for exploring solution space systematically.
Overview¶
MCTS uses:
- Tree Structure: Represents problem states
- Exploration: UCB-based node selection
- Simulation: Random playouts from nodes
- Backpropagation: Update statistics
When to Use MCTS¶
- Complex multi-step problems
- Game-like reasoning tasks
- Dialogue systems
- Exploration-exploitation tradeoff needed
Configuration¶
Rust
pub struct MCTSConfig {
pub num_iterations: usize,
pub exploration_constant: f32, // UCB parameter
pub max_depth: usize,
pub simulation_rollouts: usize,
}
Example¶
Rust
let config = MCTSConfig::default();
let mcts = MCTS::new(config);
let result = mcts.optimize(query, client).await?;