Clear Thought 1.5

/** * Monte Carlo Tree Search (MCTS) Pattern Handler Implementation * * Combines tree exploration with random sampling for decision-making * under uncertainty using selection, expansion, simulation, and backpropagation. */ import { MCTSNode, MCTSSession, MCTSConfig, MCTSOperations, ActionStatistics } from '../../types/reasoning-patterns/mcts.js'; import { ThoughtData } from '../../types/index.js'; export declare class MCTSHandler implements MCTSOperations { private readonly defaultConfig; private readonly defaultTerminationCriteria; /** * Initialize a new MCTS session */ initializeSession(explorationConstant?: number, config?: Partial<MCTSConfig>): MCTSSession; /** * Generate initial actions for root node */ private generateInitialActions; /** * Select a leaf node using UCB */ selectLeaf(session: MCTSSession): MCTSNode; /** * Check if node is a leaf (has untried actions or no children) */ private isLeaf; /** * Select best child using UCB formula */ private selectBestChild; /** * Calculate UCB score for a node */ calculateUCB(nodeId: string, parentVisits: number, session: MCTSSession): number; /** * Calculate variance for UCB1-Tuned */ private calculateVariance; /** * Get RAVE statistics for an action */ private getRAVEStatistics; /** * Expand a node by adding a child */ expandNode(nodeId: string, session: MCTSSession): MCTSNode; /** * Generate actions for a given state */ private generateActionsForState; /** * Check if state is terminal */ private isTerminalState; /** * Get state representation for a node */ private getStateRepresentation; /** * Simulate from a node to terminal state */ simulate(nodeId: string, session: MCTSSession): number; /** * Random rollout policy */ private randomRollout; /** * Heuristic-based rollout policy */ private heuristicRollout; /** * Neural network guided rollout (placeholder) */ private neuralRollout; /** * Evaluate heuristic value for a state */ private evaluateHeuristic; /** * Backpropagate simulation results */ backpropagate(leafNodeId: string, value: number, session: MCTSSession): void; /** * Get best action from root */ getBestAction(session: MCTSSession): string; /** * Get action probabilities from a node */ getActionProbabilities(nodeId: string, session: MCTSSession): Map<string, number>; /** * Run one complete MCTS iteration */ runIteration(session: MCTSSession): void; /** * Check termination criteria */ private checkTermination; /** * Update session statistics */ private updateStatistics; /** * Export to sequential thinking format */ exportToSequentialFormat(session: MCTSSession): ThoughtData[]; /** * Get best path through the tree */ private getBestPath; /** * Import from sequential thinking format */ importFromSequentialFormat(thoughts: ThoughtData[]): MCTSSession; /** * Get action statistics for analysis */ getActionStatistics(session: MCTSSession): ActionStatistics[]; } export default MCTSHandler; //# sourceMappingURL=mcts.d.ts.map