/**
 * Queen Agent - Sophisticated Collective Intelligence Leader
 * Implements advanced consensus algorithms and hive-mind coordination
 */

import { EventEmitter } from 'node:events';
import { ILogger } from '../core/logger.ts';
import { IEventBus } from '../core/event-bus.ts';
import { AgentState, TaskDefinition, TaskResult, AgentId } from '../swarm/types.ts';
import { NeuralPatternEngine } from '../coordination/neural-pattern-engine.ts';
import { generateId } from '../utils/helpers.ts';

export interface QueenDecision {
  id: string;
  type: 'task_assignment' | 'resource_allocation' | 'strategy_change' | 'agent_spawn' | 'consensus_vote';
  description: string;
  options: DecisionOption[];
  selectedOption: string;
  confidence: number;
  reasoning: string;
  consensusLevel: number;
  timestamp: Date;
  participants: string[];
  outcome: 'success' | 'failure' | 'pending';
  metadata: Record<string, any>;
}

export interface DecisionOption {
  id: string;
  description: string;
  expectedOutcome: string;
  riskLevel: number;
  resourceCost: number;
  timeEstimate: number;
  votes: number;
  supporters: string[];
  confidence: number;
}

export interface ConsensusVote {
  agentId: string;
  decisionId: string;
  optionId: string;
  weight: number;
  reasoning: string;
  confidence: number;
  timestamp: Date;
}

export interface CollectiveIntelligence {
  swarmId: string;
  totalAgents: number;
  activeAgents: number;
  averageIntelligence: number;
  consensusThreshold: number;
  decisionHistory: QueenDecision[];
  knowledgeBase: Map<string, any>;
  emergentBehaviors: string[];
  coordinationPatterns: string[];
  performanceMetrics: {
    decisionsPerHour: number;
    consensusRate: number;
    successRate: number;
    averageResponseTime: number;
    swarmEfficiency: number;
  };
}

export interface QueenConfig {
  consensusThreshold: number;
  maxDecisionTime: number;
  intelligenceWeighting: boolean;
  emergentBehaviorDetection: boolean;
  adaptiveLearning: boolean;
  democraticVoting: boolean;
  expertiseWeighting: boolean;
  realTimeConsensus: boolean;
  conflictResolution: 'majority' | 'weighted' | 'expertise' | 'neural';
  decisionCaching: boolean;
}

/**
 * Queen Agent - Leads collective intelligence with sophisticated consensus
 */
export class QueenAgent extends EventEmitter {
  private logger: ILogger;
  private eventBus: IEventBus;
  private neuralEngine: NeuralPatternEngine;
  private config: QueenConfig;
  
  // Core Queen state
  private queenId: string;
  private swarmId: string;
  private collectiveIntelligence!: CollectiveIntelligence;
  
  // Agent management
  private agents = new Map<string, AgentState>();
  private agentHierarchy = new Map<string, string[]>(); // parent -> children
  private agentExpertise = new Map<string, Record<string, number>>();
  private agentReputation = new Map<string, number>();
  
  // Decision making
  private activeDecisions = new Map<string, QueenDecision>();
  private decisionHistory: QueenDecision[] = [];
  private consensusVotes = new Map<string, ConsensusVote[]>();
  private decisionCache = new Map<string, QueenDecision>();
  
  // Collective intelligence
  private knowledgeGraph = new Map<string, any>();
  private emergentPatterns = new Map<string, any>();
  private coordinationStrategies = new Map<string, any>();
  private swarmMetrics = new Map<string, number>();
  
  // Advanced algorithms
  private consensusAlgorithms = new Map<string, (votes: ConsensusVote[]) => string>();
  private conflictResolvers = new Map<string, (conflicts: any[]) => any>();
  private emergencyProtocols = new Map<string, () => Promise<void>>();
  
  constructor(
    swarmId: string,
    config: Partial<QueenConfig>,
    logger: ILogger,
    eventBus: IEventBus,
    neuralEngine: NeuralPatternEngine
  ) {
    super();
    this.logger = logger;
    this.eventBus = eventBus;
    this.neuralEngine = neuralEngine;
    this.queenId = generateId('queen');
    this.swarmId = swarmId;
    
    this.config = {
      consensusThreshold: 0.7,
      maxDecisionTime: 30000, // 30 seconds
      intelligenceWeighting: true,
      emergentBehaviorDetection: true,
      adaptiveLearning: true,
      democraticVoting: true,
      expertiseWeighting: true,
      realTimeConsensus: true,
      conflictResolution: 'neural',
      decisionCaching: true,
      ...config
    };
    
    this.initializeQueen();
  }
  
  private async initializeQueen(): Promise<void> {
    // Initialize collective intelligence
    this.collectiveIntelligence = {
      swarmId: this.swarmId,
      totalAgents: 0,
      activeAgents: 0,
      averageIntelligence: 0,
      consensusThreshold: this.config.consensusThreshold,
      decisionHistory: [],
      knowledgeBase: new Map(),
      emergentBehaviors: [],
      coordinationPatterns: [],
      performanceMetrics: {
        decisionsPerHour: 0,
        consensusRate: 0,
        successRate: 0,
        averageResponseTime: 0,
        swarmEfficiency: 0
      }
    };
    
    // Initialize consensus algorithms
    this.initializeConsensusAlgorithms();
    
    // Initialize conflict resolution
    this.initializeConflictResolvers();
    
    // Initialize emergency protocols
    this.initializeEmergencyProtocols();
    
    // Setup event handlers
    this.setupEventHandlers();
    
    // Start Queen processes
    this.startQueenProcesses();
    
    this.logger.info('Queen Agent initialized', {
      queenId: this.queenId,
      swarmId: this.swarmId,
      config: this.config
    });
  }
  
  private initializeConsensusAlgorithms(): void {
    // Majority voting
    this.consensusAlgorithms.set('majority', (votes: ConsensusVote[]) => {
      const optionCounts = new Map<string, number>();
      votes.forEach(vote => {
        optionCounts.set(vote.optionId, (optionCounts.get(vote.optionId) || 0) + 1);
      });
      
      let maxCount = 0;
      let selectedOption = '';
      for (const [optionId, count] of optionCounts) {
        if (count > maxCount) {
          maxCount = count;
          selectedOption = optionId;
        }
      }
      
      return selectedOption;
    });
    
    // Weighted voting by expertise
    this.consensusAlgorithms.set('weighted', (votes: ConsensusVote[]) => {
      const optionScores = new Map<string, number>();
      votes.forEach(vote => {
        const currentScore = optionScores.get(vote.optionId) || 0;
        optionScores.set(vote.optionId, currentScore + (vote.weight * vote.confidence));
      });
      
      let maxScore = 0;
      let selectedOption = '';
      for (const [optionId, score] of optionScores) {
        if (score > maxScore) {
          maxScore = score;
          selectedOption = optionId;
        }
      }
      
      return selectedOption;
    });
    
    // Expertise-based consensus
    this.consensusAlgorithms.set('expertise', (votes: ConsensusVote[]) => {
      const expertiseWeights = new Map<string, number>();
      votes.forEach(vote => {
        const agentExpertise = this.agentExpertise.get(vote.agentId) || {};
        const expertiseLevel = Object.values(agentExpertise).reduce((a, b) => a + b, 0) / Object.keys(agentExpertise).length || 0.5;
        expertiseWeights.set(vote.optionId, (expertiseWeights.get(vote.optionId) || 0) + expertiseLevel);
      });
      
      let maxWeight = 0;
      let selectedOption = '';
      for (const [optionId, weight] of expertiseWeights) {
        if (weight > maxWeight) {
          maxWeight = weight;
          selectedOption = optionId;
        }
      }
      
      return selectedOption;
    });
    
    // Neural network consensus
    this.consensusAlgorithms.set('neural', (votes: ConsensusVote[]) => {
      // Use neural pattern engine for consensus
      const features = votes.map(vote => [vote.weight, vote.confidence]);
      // This would use the neural engine to predict best option
      // For now, fall back to weighted voting
      return this.consensusAlgorithms.get('weighted')!(votes);
    });
  }
  
  private initializeConflictResolvers(): void {
    // Simple conflict resolution
    this.conflictResolvers.set('simple', (conflicts: any[]) => {
      // Return first non-conflicting option
      return conflicts[0];
    });
    
    // Negotiation-based resolution
    this.conflictResolvers.set('negotiation', (conflicts: any[]) => {
      // Find compromise solution
      const compromise = conflicts.reduce((acc, conflict) => {
        // Merge conflict properties
        return { ...acc, ...conflict };
      }, {});
      
      return compromise;
    });
    
    // Authority-based resolution
    this.conflictResolvers.set('authority', (conflicts: any[]) => {
      // Queen makes final decision
      return conflicts[0]; // Queen's preference
    });
  }
  
  private initializeEmergencyProtocols(): void {
    // Agent failure protocol
    this.emergencyProtocols.set('agent_failure', async () => {
      this.logger.warn('Emergency: Agent failure detected');
      await this.redistributeTasks();
      await this.spawnReplacementAgent();
    });
    
    // Consensus deadlock protocol
    this.emergencyProtocols.set('consensus_deadlock', async () => {
      this.logger.warn('Emergency: Consensus deadlock detected');
      await this.breakDeadlock();
    });
    
    // Resource exhaustion protocol
    this.emergencyProtocols.set('resource_exhaustion', async () => {
      this.logger.warn('Emergency: Resource exhaustion detected');
      await this.optimizeResourceUsage();
    });
    
    // Swarm fragmentation protocol
    this.emergencyProtocols.set('swarm_fragmentation', async () => {
      this.logger.warn('Emergency: Swarm fragmentation detected');
      await this.reunifySwarm();
    });
  }
  
  private setupEventHandlers(): void {
    // Agent registration
    this.eventBus.on('agent:registered', (agent: AgentState) => {
      this.registerAgent(agent);
    });
    
    // Agent status changes
    this.eventBus.on('agent:status_change', (data: { agentId: string; status: string }) => {
      this.handleAgentStatusChange(data.agentId, data.status);
    });
    
    // Task completion
    this.eventBus.on('task:completed', (data: { task: TaskDefinition; result: TaskResult; agent: AgentState }) => {
      this.learnFromTaskCompletion(data.task, data.result, data.agent);
    });
    
    // Consensus votes
    this.eventBus.on('consensus:vote', (vote: ConsensusVote) => {
      this.processConsensusVote(vote);
    });
    
    // Emergency signals
    this.eventBus.on('emergency:signal', (data: { type: string; details: any }) => {
      this.handleEmergency(data.type, data.details);
    });
  }
  
  private startQueenProcesses(): void {
    // Collective intelligence monitoring
    setInterval(() => {
      this.updateCollectiveIntelligence();
    }, 5000);
    
    // Emergent behavior detection
    setInterval(() => {
      this.detectEmergentBehaviors();
    }, 10000);
    
    // Performance optimization
    setInterval(() => {
      this.optimizeSwarmPerformance();
    }, 30000);
    
    // Decision cleanup
    setInterval(() => {
      this.cleanupCompletedDecisions();
    }, 60000);
  }
  
  /**
   * Make a collective decision with consensus
   */
  async makeDecision(
    type: QueenDecision['type'],
    description: string,
    options: Omit<DecisionOption, 'votes' | 'supporters' | 'confidence'>[]
  ): Promise<QueenDecision> {
    const decisionId = generateId('decision');
    
    // Check decision cache
    const cacheKey = `${type}:${description}`;
    if (this.config.decisionCaching && this.decisionCache.has(cacheKey)) {
      const cached = this.decisionCache.get(cacheKey)!;
      this.logger.debug('Using cached decision', { decisionId: cached.id });
      return cached;
    }
    
    const decision: QueenDecision = {
      id: decisionId,
      type,
      description,
      options: options.map(opt => ({
        ...opt,
        votes: 0,
        supporters: [],
        confidence: 0
      })),
      selectedOption: '',
      confidence: 0,
      reasoning: '',
      consensusLevel: 0,
      timestamp: new Date(),
      participants: [],
      outcome: 'pending',
      metadata: {}
    };
    
    this.activeDecisions.set(decisionId, decision);
    
    // Initiate consensus process
    await this.initiateConsensus(decision);
    
    // Wait for consensus or timeout
    const result = await this.waitForConsensus(decisionId);
    
    // Cache successful decisions
    if (result.outcome === 'success' && this.config.decisionCaching) {
      this.decisionCache.set(cacheKey, result);
    }
    
    return result;
  }
  
  private async initiateConsensus(decision: QueenDecision): Promise<void> {
    this.logger.info('Initiating consensus', {
      decisionId: decision.id,
      type: decision.type,
      options: decision.options.length
    });
    
    // Notify all agents about the decision
    this.eventBus.emit('consensus:initiated', {
      decision,
      deadline: new Date(Date.now() + this.config.maxDecisionTime)
    });
    
    // If neural pattern engine is available, get AI recommendation
    if (this.neuralEngine) {
      try {
        const recommendation = await this.getNeuralRecommendation(decision);
        this.logger.debug('Neural recommendation received', {
          decisionId: decision.id,
          recommendation: recommendation.reasoning
        });
      } catch (error) {
        this.logger.warn('Neural recommendation failed', { error });
      }
    }
  }
  
  private async waitForConsensus(decisionId: string): Promise<QueenDecision> {
    return new Promise((resolve) => {
      const timeout = setTimeout(() => {
        const decision = this.activeDecisions.get(decisionId)!;
        decision.outcome = 'failure';
        decision.reasoning = 'Consensus timeout';
        this.activeDecisions.delete(decisionId);
        resolve(decision);
      }, this.config.maxDecisionTime);
      
      // Check for consensus periodically
      const checkConsensus = setInterval(() => {
        const decision = this.activeDecisions.get(decisionId);
        if (!decision) {
          clearInterval(checkConsensus);
          clearTimeout(timeout);
          return;
        }
        
        const votes = this.consensusVotes.get(decisionId) || [];
        const consensusLevel = this.calculateConsensusLevel(votes);
        
        if (consensusLevel >= this.config.consensusThreshold) {
          // Consensus reached
          const selectedOption = this.applyConsensusAlgorithm(votes);
          
          decision.selectedOption = selectedOption;
          decision.consensusLevel = consensusLevel;
          decision.confidence = this.calculateDecisionConfidence(votes);
          decision.reasoning = this.generateDecisionReasoning(votes, selectedOption);
          decision.outcome = 'success';
          decision.participants = votes.map(v => v.agentId);
          
          this.activeDecisions.delete(decisionId);
          this.decisionHistory.push(decision);
          
          clearInterval(checkConsensus);
          clearTimeout(timeout);
          resolve(decision);
        }
      }, 1000);
    });
  }
  
  private processConsensusVote(vote: ConsensusVote): void {
    const votes = this.consensusVotes.get(vote.decisionId) || [];
    
    // Remove any existing vote from this agent
    const filteredVotes = votes.filter(v => v.agentId !== vote.agentId);
    filteredVotes.push(vote);
    
    this.consensusVotes.set(vote.decisionId, filteredVotes);
    
    // Update decision option votes
    const decision = this.activeDecisions.get(vote.decisionId);
    if (decision) {
      const option = decision.options.find(opt => opt.id === vote.optionId);
      if (option) {
        option.votes = filteredVotes.filter(v => v.optionId === vote.optionId).length;
        option.supporters = filteredVotes.filter(v => v.optionId === vote.optionId).map(v => v.agentId);
        option.confidence = filteredVotes
          .filter(v => v.optionId === vote.optionId)
          .reduce((sum, v) => sum + v.confidence, 0) / option.votes || 0;
      }
    }
    
    this.logger.debug('Consensus vote processed', {
      decisionId: vote.decisionId,
      agentId: vote.agentId,
      optionId: vote.optionId,
      totalVotes: filteredVotes.length
    });
  }
  
  private calculateConsensusLevel(votes: ConsensusVote[]): number {
    if (votes.length === 0) return 0;
    
    const activeAgents = this.collectiveIntelligence.activeAgents;
    const participationRate = votes.length / Math.max(activeAgents, 1);
    
    // Group votes by option
    const optionVotes = new Map<string, number>();
    votes.forEach(vote => {
      optionVotes.set(vote.optionId, (optionVotes.get(vote.optionId) || 0) + 1);
    });
    
    // Find highest vote count
    const maxVotes = Math.max(...optionVotes.values());
    const consensusRate = maxVotes / votes.length;
    
    return participationRate * consensusRate;
  }
  
  private applyConsensusAlgorithm(votes: ConsensusVote[]): string {
    const algorithm = this.consensusAlgorithms.get(this.config.conflictResolution);
    if (!algorithm) {
      throw new Error(`Unknown consensus algorithm: ${this.config.conflictResolution}`);
    }
    
    return algorithm(votes);
  }
  
  private calculateDecisionConfidence(votes: ConsensusVote[]): number {
    if (votes.length === 0) return 0;
    
    const avgConfidence = votes.reduce((sum, vote) => sum + vote.confidence, 0) / votes.length;
    const consensusLevel = this.calculateConsensusLevel(votes);
    
    return (avgConfidence + consensusLevel) / 2;
  }
  
  private generateDecisionReasoning(votes: ConsensusVote[], selectedOption: string): string {
    const supportingVotes = votes.filter(v => v.optionId === selectedOption);
    const avgConfidence = supportingVotes.reduce((sum, v) => sum + v.confidence, 0) / supportingVotes.length;
    
    return `Selected option ${selectedOption} with ${supportingVotes.length} votes (${(avgConfidence * 100).toFixed(1)}% confidence)`;
  }
  
  private async getNeuralRecommendation(decision: QueenDecision): Promise<any> {
    // This would use the neural pattern engine to provide AI recommendations
    // For now, return a simple recommendation
    return {
      recommendedOption: decision.options[0]?.id,
      reasoning: 'Neural analysis suggests this option has highest success probability',
      confidence: 0.8
    };
  }
  
  private registerAgent(agent: AgentState): void {
    this.agents.set(agent.id.id, agent);
    this.collectiveIntelligence.totalAgents++;
    this.collectiveIntelligence.activeAgents++;
    
    // Initialize agent reputation
    this.agentReputation.set(agent.id.id, 0.5);
    
    // Extract agent expertise
    const expertise: Record<string, number> = {};
    Object.entries(agent.capabilities).forEach(([key, value]) => {
      if (typeof value === 'number') {
        expertise[key] = value;
      } else if (typeof value === 'boolean' && value) {
        expertise[key] = 0.8;
      }
    });
    this.agentExpertise.set(agent.id.id, expertise);
    
    this.logger.info('Agent registered with Queen', {
      agentId: agent.id.id,
      type: agent.type,
      expertise: Object.keys(expertise)
    });
    
    this.emit('agent:registered', agent);
  }
  
  private handleAgentStatusChange(agentId: string, status: string): void {
    const agent = this.agents.get(agentId);
    if (!agent) return;
    
    agent.status = status as any;
    
    // Update active agent count
    if (status === 'idle' || status === 'busy') {
      this.collectiveIntelligence.activeAgents = Array.from(this.agents.values())
        .filter(a => a.status === 'idle' || a.status === 'busy').length;
    }
    
    this.logger.debug('Agent status changed', { agentId, status });
  }
  
  private learnFromTaskCompletion(task: TaskDefinition, result: TaskResult, agent: AgentState): void {
    // Update agent reputation based on task success
    const currentReputation = this.agentReputation.get(agent.id.id) || 0.5;
    const taskSuccess = result.accuracy && result.accuracy > 0.7 ? 1 : 0;
    const newReputation = (currentReputation * 0.9) + (taskSuccess * 0.1);
    
    this.agentReputation.set(agent.id.id, newReputation);
    
    // Update collective intelligence metrics
    this.updateCollectiveIntelligence();
    
    this.logger.debug('Learned from task completion', {
      agentId: agent.id.id,
      taskSuccess,
      newReputation: newReputation.toFixed(3)
    });
  }
  
  private updateCollectiveIntelligence(): void {
    const agents = Array.from(this.agents.values());
    
    // Calculate average intelligence
    const totalIntelligence = agents.reduce((sum, agent) => {
      const reputation = this.agentReputation.get(agent.id.id) || 0.5;
      return sum + (agent.metrics.successRate * reputation);
    }, 0);
    
    this.collectiveIntelligence.averageIntelligence = totalIntelligence / Math.max(agents.length, 1);
    
    // Update performance metrics
    const now = Date.now();
    const hourAgo = now - 3600000;
    const recentDecisions = this.decisionHistory.filter(d => d.timestamp.getTime() > hourAgo);
    
    this.collectiveIntelligence.performanceMetrics = {
      decisionsPerHour: recentDecisions.length,
      consensusRate: recentDecisions.filter(d => d.consensusLevel >= this.config.consensusThreshold).length / Math.max(recentDecisions.length, 1),
      successRate: recentDecisions.filter(d => d.outcome === 'success').length / Math.max(recentDecisions.length, 1),
      averageResponseTime: recentDecisions.reduce((sum, d) => sum + (d.timestamp.getTime() - d.timestamp.getTime()), 0) / Math.max(recentDecisions.length, 1),
      swarmEfficiency: this.collectiveIntelligence.averageIntelligence * this.collectiveIntelligence.performanceMetrics.consensusRate
    };
  }
  
  private detectEmergentBehaviors(): void {
    // Analyze patterns in agent behavior and decisions
    const agents = Array.from(this.agents.values());
    const patterns = new Map<string, number>();
    
    // Look for coordination patterns
    agents.forEach(agent => {
      const behaviorKey = `${agent.type}:${agent.status}`;
      patterns.set(behaviorKey, (patterns.get(behaviorKey) || 0) + 1);
    });
    
    // Identify emergent behaviors
    const emergentBehaviors: string[] = [];
    for (const [pattern, count] of patterns) {
      if (count > agents.length * 0.3) { // 30% threshold
        emergentBehaviors.push(pattern);
      }
    }
    
    this.collectiveIntelligence.emergentBehaviors = emergentBehaviors;
    
    if (emergentBehaviors.length > 0) {
      this.logger.info('Emergent behaviors detected', { behaviors: emergentBehaviors });
      this.emit('emergent:behaviors', emergentBehaviors);
    }
  }
  
  private async optimizeSwarmPerformance(): Promise<void> {
    const metrics = this.collectiveIntelligence.performanceMetrics;
    
    // Identify optimization opportunities
    if (metrics.consensusRate < 0.7) {
      await this.optimizeConsensusProcess();
    }
    
    if (metrics.averageResponseTime > 10000) {
      await this.optimizeResponseTime();
    }
    
    if (metrics.swarmEfficiency < 0.6) {
      await this.optimizeSwarmStructure();
    }
  }
  
  private async optimizeConsensusProcess(): Promise<void> {
    // Adjust consensus threshold based on performance
    const currentThreshold = this.config.consensusThreshold;
    const newThreshold = Math.max(0.5, currentThreshold - 0.1);
    
    this.config.consensusThreshold = newThreshold;
    this.collectiveIntelligence.consensusThreshold = newThreshold;
    
    this.logger.info('Consensus threshold optimized', {
      previous: currentThreshold,
      new: newThreshold
    });
  }
  
  private async optimizeResponseTime(): Promise<void> {
    // Reduce decision timeout for faster responses
    const currentTimeout = this.config.maxDecisionTime;
    const newTimeout = Math.max(10000, currentTimeout - 5000);
    
    this.config.maxDecisionTime = newTimeout;
    
    this.logger.info('Response time optimized', {
      previous: currentTimeout,
      new: newTimeout
    });
  }
  
  private async optimizeSwarmStructure(): Promise<void> {
    // Analyze agent distribution and suggest restructuring
    const agents = Array.from(this.agents.values());
    const typeDistribution = new Map<string, number>();
    
    agents.forEach(agent => {
      typeDistribution.set(agent.type, (typeDistribution.get(agent.type) || 0) + 1);
    });
    
    this.logger.info('Swarm structure analysis', {
      totalAgents: agents.length,
      distribution: Object.fromEntries(typeDistribution)
    });
    
    // Suggest spawning additional agents if needed
    if (agents.length < 3) {
      this.emit('swarm:suggestion', {
        type: 'spawn_agent',
        reason: 'Insufficient agent count for optimal performance'
      });
    }
  }
  
  private cleanupCompletedDecisions(): void {
    const cutoff = Date.now() - 3600000; // 1 hour ago
    
    this.decisionHistory = this.decisionHistory.filter(decision => 
      decision.timestamp.getTime() > cutoff
    );
    
    // Clean up consensus votes for old decisions
    for (const [decisionId, votes] of this.consensusVotes) {
      const decision = this.decisionHistory.find(d => d.id === decisionId);
      if (!decision) {
        this.consensusVotes.delete(decisionId);
      }
    }
  }
  
  private async handleEmergency(type: string, details: any): Promise<void> {
    const protocol = this.emergencyProtocols.get(type);
    if (protocol) {
      await protocol();
    } else {
      this.logger.warn('Unknown emergency type', { type, details });
    }
  }
  
  private async redistributeTasks(): Promise<void> {
    // Redistribute tasks from failed agents
    this.logger.info('Redistributing tasks due to agent failure');
    // Implementation would redistribute active tasks
  }
  
  private async spawnReplacementAgent(): Promise<void> {
    // Spawn new agent to replace failed one
    this.logger.info('Spawning replacement agent');
    this.emit('agent:spawn_request', { reason: 'replacement' });
  }
  
  private async breakDeadlock(): Promise<void> {
    // Break consensus deadlock by Queen decision
    this.logger.info('Breaking consensus deadlock');
    
    for (const [decisionId, decision] of this.activeDecisions) {
      if (decision.outcome === 'pending') {
        // Queen makes executive decision
        decision.selectedOption = decision.options[0]?.id || '';
        decision.outcome = 'success';
        decision.reasoning = 'Queen executive decision due to deadlock';
        decision.confidence = 0.6;
        
        this.activeDecisions.delete(decisionId);
        this.decisionHistory.push(decision);
        
        this.emit('decision:executive', decision);
      }
    }
  }
  
  private async optimizeResourceUsage(): Promise<void> {
    // Optimize resource usage across swarm
    this.logger.info('Optimizing resource usage');
    this.emit('swarm:optimize_resources', {});
  }
  
  private async reunifySwarm(): Promise<void> {
    // Reunify fragmented swarm
    this.logger.info('Reunifying fragmented swarm');
    this.emit('swarm:reunify', {});
  }
  
  /**
   * Get collective intelligence status
   */
  getCollectiveIntelligence(): CollectiveIntelligence {
    return { ...this.collectiveIntelligence };
  }
  
  /**
   * Get agent reputation
   */
  getAgentReputation(agentId: string): number {
    return this.agentReputation.get(agentId) || 0.5;
  }
  
  /**
   * Get decision history
   */
  getDecisionHistory(): QueenDecision[] {
    return [...this.decisionHistory];
  }
  
  /**
   * Get active decisions
   */
  getActiveDecisions(): QueenDecision[] {
    return Array.from(this.activeDecisions.values());
  }
  
  /**
   * Shutdown Queen agent
   */
  async shutdown(): Promise<void> {
    // Complete any pending decisions
    for (const [decisionId, decision] of this.activeDecisions) {
      decision.outcome = 'failure';
      decision.reasoning = 'Queen shutdown';
      this.decisionHistory.push(decision);
    }
    
    this.activeDecisions.clear();
    this.consensusVotes.clear();
    this.agents.clear();
    
    this.logger.info('Queen Agent shutdown complete');
  }
}