@polybiouslabs/polybious/dist/core/behavioral-evolution.d.ts

Polybius is a next-generation intelligent agent framework built for adaptability across diverse domains. It merges contextual awareness, multi-agent collaboration, and predictive reasoning to deliver dynamic, self-optimizing performance.

export interface Behavior {
    action: any;
    context: any;
    value: number;
    confidence: number;
    experiences: number;
    lastUpdated: Date;
    createdAt: Date;
    personalLearningRate: number;
    contextSensitivity: number;
    explorationTendency: number;
}

export interface Experience {
    id: string;
    timestamp: Date;
    action: any;
    context: any;
    outcome: any;
    feedback: any;
    reward: number;
    processed: boolean;
}

export interface Policy {
    defaultAction: string;
    confidence: number;
    actions: Map<string, ActionData>;
    created: Date;
}

export interface ActionData {
    value: number;
    count: number;
    lastSeen: Date;
}

export interface ActionSuggestion {
    action: any;
    confidence: number;
    reasoning: string;
    explorationRate: number;
    timestamp: Date;
}

export interface Mutation {
    type: 'value_adjustment' | 'learning_rate' | 'context_sensitivity' | 'exploration_strategy';
    valueChange?: number;
    confidenceChange?: number;
    learningRateMultiplier?: number;
    sensitivityChange?: number;
    explorationMultiplier?: number;
}

export interface EvolutionRoundResult {
    round: number;
    mutationsTested: number;
    improvements: number;
    bestImprovement: number;
    improvementDetails: Array<{
        behaviorKey: string;
        improvement: number;
        mutation: Mutation;
    }>;
}

export interface EvolutionResult {
    rounds: number;
    results: EvolutionRoundResult[];
    overallImprovement: {
        totalImprovements: number;
        avgImprovementPerRound: number;
        bestImprovement: number;
        consistency: number;
    };
    finalStats: BehaviorStats;
}

export interface BehaviorStats {
    totalBehaviors: number;
    totalPolicies: number;
    totalExperiences: number;
    averageConfidence: number;
    learningRate: number;
    explorationRate: number;
    topBehaviors: Array<{
        behaviorKey: string;
        value: number;
        confidence: number;
        experiences: number;
    }>;
    recentLearning: {
        recentExperiences: number;
        averageReward: number;
        positiveExperiences: number;
        negativeExperiences: number;
    };
}

export declare class BehavioralEvolutionModel {
    behaviors: Map<string, Behavior>;
    rewards: Map<string, any>;
    policies: Map<string, Policy>;
    experiences: Experience[];
    evolutionPath: string;
    learningRate: number;
    explorationRate: number;
    decayRate: number;

    constructor(learningRate?: number, explorationRate?: number, decayRate?: number);
    recordExperience(action: any, context: any, outcome: any, feedback: any): Promise<string>;
    processExperience(experience: Experience): Promise<void>;
    suggestAction(context: any, availableActions?: any[]): Promise<ActionSuggestion>;
    evolveStrategy(evolutionRounds?: number): Promise<EvolutionResult>;
    performEvolutionRound(roundNumber: number): Promise<EvolutionRoundResult>;
    generateMutation(behavior: Behavior): Mutation;
    testMutation(mutationData: any): Promise<{ improvement: number; confidence: number; mutated?: Behavior }>;
    applyMutation(behavior: Behavior, mutation: Mutation): Behavior;
    calculateBehaviorPerformance(behavior: Behavior, experiences: Experience[]): number;
    applyEvolutionResults(roundResults: EvolutionRoundResult): Promise<void>;
    calculateReward(outcome: any, feedback: any): number;
    normalizeContext(context: any): any;
    getBehaviorKey(action: any, context: any): string;
    getContextKey(context: any): string;
    createNewBehavior(action: any, context: any): Behavior;
    updateBehavior(behavior: Behavior, reward: number): void;
    createDefaultPolicy(): Policy;
    updatePolicies(action: any, context: any, reward: number): Promise<void>;
    getBestAction(policy: Policy, availableActions: any[], context: any): any;
    generateExploratoryAction(context: any): string;
    calculateActionConfidence(action: any, context: any): number;
    explainActionChoice(action: any, policy: Policy, context: any): string;
    calculateOverallImprovement(evolutionResults: EvolutionRoundResult[]): any;
    calculateImprovementConsistency(evolutionResults: EvolutionRoundResult[]): number;
    calculateAverageConfidence(): number;
    getBehaviorStats(): BehaviorStats;
    getTopBehaviors(limit?: number): Array<{
        behaviorKey: string;
        value: number;
        confidence: number;
        experiences: number;
    }>;
    getRecentLearningStats(): {
        recentExperiences: number;
        averageReward: number;
        positiveExperiences: number;
        negativeExperiences: number;
    };
    initializeBehaviors(): void;
    loadEvolutionData(): Promise<void>;
    saveEvolutionData(): Promise<void>;
}