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

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

import { MLBehaviorModel, MLAgentState, AgentAction } from '../interfaces';
/**
 * Generic network formation ML model for social connections
 * Works for friendship networks, collaboration networks, or any social structure
 */
export declare class NetworkFormationModel implements MLBehaviorModel {
    private model?;
    private inputFeatures;
    private outputActions;
    private isLoaded;
    private homophilyStrength;
    private proximityWeight;
    private popularityBias;
    constructor();
    predict(state: MLAgentState): Promise<AgentAction>;
    /**
     * ML-based prediction
     */
    private predictWithML;
    /**
     * Rule-based network formation prediction
     */
    private predictWithRules;
    /**
     * Find potential agents to connect with
     */
    private findConnectionCandidates;
    /**
     * Get current connections of the agent
     */
    private getCurrentConnections;
    /**
     * Get maximum number of connections this agent can maintain
     */
    private getMaxConnections;
    /**
     * Evaluate a potential connection candidate
     */
    private evaluateConnectionCandidate;
    /**
     * Calculate similarity between two agents
     */
    private calculateSimilarity;
    /**
     * Count mutual connections between two agents
     */
    private countMutualConnections;
    /**
     * Create connection action
     */
    private createConnectionAction;
    /**
     * Create disconnection action
     */
    private createDisconnectionAction;
    /**
     * Create maintenance action for existing connections
     */
    private createMaintenanceAction;
    /**
     * Create no-action response
     */
    private createNoActionResponse;
    /**
     * Determine type of connection to form
     */
    private determineConnectionType;
    /**
     * Evaluate candidates using ML model
     */
    private evaluateCandidatesWithML;
    /**
     * Create network action from ML evaluation
     */
    private createNetworkAction;
    /**
     * Encode agent state and candidate for ML model
     */
    private encodeNetworkState;
    load(modelPath: string): Promise<void>;
    getRequiredInputs(): string[];
    getOutputActions(): string[];
    dispose(): void;
    /**
     * Configure network formation parameters
     */
    configure(options: {
        homophilyStrength?: number;
        proximityWeight?: number;
        popularityBias?: number;
    }): void;
    /**
     * Generate training data for network formation model
     */
    generateTrainingData(scenarios: Array<{
        agentCount: number;
        networkDensity: 'sparse' | 'medium' | 'dense';
        homophilyLevel: 'low' | 'medium' | 'high';
    }>, stepsPerScenario?: number): Array<{
        input: number[];
        output: number[];
    }>;
    /**
     * Generate mock network state for training
     */
    private generateMockNetworkState;
}
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