agentjs-core/dist/ml/models/EconomicMLModel.d.ts

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

import { MLBehaviorModel, MLAgentState, AgentAction } from '../interfaces';
/**
 * Generic economic agent ML model for trading and resource decisions
 * Works for market trading, resource allocation, or economic simulations
 */
export declare class EconomicMLModel implements MLBehaviorModel {
    private model?;
    private inputFeatures;
    private outputActions;
    private isLoaded;
    private riskTolerance;
    private greedFactor;
    private socialInfluence;
    constructor();
    predict(state: MLAgentState): Promise<AgentAction>;
    /**
     * ML-based prediction
     */
    private predictWithML;
    /**
     * Rule-based economic prediction (fallback and training data generation)
     */
    private predictWithRules;
    /**
     * Make economic decision based on current conditions
     */
    private makeEconomicDecision;
    /**
     * Create agent action from economic decision
     */
    private createEconomicAction;
    /**
     * Get current market price from environment or agent properties
     */
    private getMarketPrice;
    /**
     * Get price history for trend analysis
     */
    private getPriceHistory;
    /**
     * Calculate price trend (positive = rising, negative = falling)
     */
    private calculatePriceTrend;
    /**
     * Calculate price volatility
     */
    private calculateVolatility;
    /**
     * Analyze neighbor economic behavior
     */
    private analyzeNeighborBehavior;
    /**
     * Encode agent state for ML model input
     */
    private encodeEconomicState;
    /**
     * Calculate relative wealth rank among neighbors
     */
    private calculateWealthRank;
    /**
     * Decode ML output to economic action
     */
    private decodeEconomicAction;
    load(modelPath: string): Promise<void>;
    getRequiredInputs(): string[];
    getOutputActions(): string[];
    dispose(): void;
    /**
     * Configure economic behavior parameters
     */
    configure(options: {
        riskTolerance?: number;
        greedFactor?: number;
        socialInfluence?: number;
    }): void;
    /**
     * Generate training data for economic model
     */
    generateTrainingData(scenarios: Array<{
        agentCount: number;
        marketConditions: 'bull' | 'bear' | 'volatile' | 'stable';
        initialWealth: {
            min: number;
            max: number;
        };
    }>, stepsPerScenario?: number): Array<{
        input: number[];
        output: number[];
    }>;
    /**
     * Generate mock economic state for training
     */
    private generateMockEconomicState;
}
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