agentjs-core/dist/ml/GenericDataCollector.d.ts

A comprehensive agent-based modeling framework with built-in p5.js visualization

import { Simulation } from '../core/Simulation';
import { TrainingDataset } from './interfaces';
/**
 * Generic data collector for ML training datasets
 */
export declare class GenericDataCollector {
    private collectedData;
    private isCollecting;
    private scenarioMetadata;
    private collectionStartTime;
    /**
     * Start collecting training data from a simulation
     * @param simulation Simulation to collect from
     * @param scenarioType Type of scenario being collected
     * @param episodes Number of episodes to collect
     */
    startCollection(_simulation: Simulation, scenarioType: string, episodes?: number): void;
    /**
     * Stop data collection
     */
    stopCollection(): void;
    /**
     * Record a single step of the simulation
     * @param simulation Current simulation state
     * @param stepNumber Current step number
     */
    recordStep(simulation: Simulation, _stepNumber: number): void;
    /**
     * Extract state-action pair from an agent
     */
    private extractStateActionPair;
    /**
     * Capture current agent state
     */
    private captureAgentState;
    /**
     * Infer agent action from property changes
     */
    private inferAgentAction;
    /**
     * Estimate movement from agent state
     */
    private estimateMovement;
    /**
     * Estimate interaction from agent state
     */
    private estimateInteraction;
    /**
     * Calculate generic reward signal
     */
    private calculateGenericReward;
    /**
     * Get neighboring agents
     */
    private getAgentNeighbors;
    /**
     * Export collected data as training dataset
     */
    exportData(): TrainingDataset;
    /**
     * Export data in specific format
     * @param format Export format
     * @returns Formatted data string
     */
    exportForTraining(format: 'tensorflow' | 'pytorch' | 'csv'): string;
    /**
     * Export to CSV format
     */
    private exportToCSV;
    /**
     * Export to TensorFlow format (JSON)
     */
    private exportToTensorFlow;
    /**
     * Export to PyTorch format (JSON)
     */
    private exportToPyTorch;
    /**
     * Get collection statistics
     */
    getCollectionStats(): {
        isCollecting: boolean;
        dataPointsCollected: number;
        collectionDuration: number;
        averageDataPointsPerSecond: number;
        metadata: TrainingDataset['metadata'] | null;
    };
    /**
     * Clear collected data
     */
    clearData(): void;
    /**
     * Save data to file (browser download)
     */
    saveToFile(filename: string, format?: 'tensorflow' | 'pytorch' | 'csv'): void;
}
//# sourceMappingURL=GenericDataCollector.d.ts.map