wifi-densepose/examples/delta-behavior/wasm/dist/index.cjs.map

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* Delta-Behavior WASM SDK\n *\n * High-level TypeScript wrapper for the delta-behavior WASM module.\n * Provides ergonomic APIs for all 10 delta-behavior applications.\n *\n * @packageDocumentation\n */\n\nimport type {\n  // Core types\n  Coherence,\n  CoherenceBounds,\n  DeltaConfig,\n  EnergyConfig,\n  GatingConfig,\n  SchedulingConfig,\n  TransitionResult,\n  SystemState,\n  WasmInitOptions,\n  Attractor,\n  GuidanceForce,\n\n  // App 1: Self-Limiting Reasoning\n  SelfLimitingReasonerConfig,\n  ReasoningContext,\n  ReasoningResult,\n  CollapseFunction,\n\n  // App 2: Event Horizons\n  EventHorizonConfig,\n  MovementResult,\n  RecursionResult,\n  Improvement,\n\n  // App 3: Homeostasis\n  Genome,\n  OrganismAction,\n  OrganismActionResult,\n  OrganismStatus,\n\n  // App 4: World Models\n  Observation,\n  WorldModelUpdateResult,\n  WorldEntity,\n  PhysicalLaw,\n\n  // App 5: Creativity\n  CreativeConstraint,\n  CreativeResult,\n  MusicalPhrase,\n\n  // App 6: Financial\n  Transaction,\n  FinancialTransactionResult,\n  Participant,\n  Position,\n  CircuitBreakerState,\n\n  // App 7: Aging\n  AgingSystemOperation,\n  AgingOperationResult,\n  Capability,\n  Node,\n  AgeThreshold,\n\n  // App 8: Swarm\n  SwarmAgent,\n  SwarmAction,\n  SwarmActionResult,\n  SwarmState,\n  CoherenceWeights,\n  SpatialBounds,\n\n  // App 9: Shutdown\n  GracefulSystemState,\n  GracefulOperationResult,\n  Resource,\n  ShutdownHook,\n  Checkpoint,\n\n  // App 10: Containment\n  CapabilityDomain,\n  GrowthResult,\n  ModificationAttempt,\n  SubstrateConfig,\n} from './types.js';\n\n// Re-export all types\nexport * from './types.js';\n\n// =============================================================================\n// WASM Module Loading\n// =============================================================================\n\nlet wasmModule: WebAssembly.Module | null = null;\nlet wasmInstance: WebAssembly.Instance | null = null;\nlet wasmMemory: WebAssembly.Memory | null = null;\n\n/**\n * Initialize the WASM module\n *\n * @param options - Initialization options\n * @returns Promise that resolves when WASM is ready\n *\n * @example\n * ```typescript\n * import { init } from '@ruvector/delta-behavior';\n *\n * await init({ wasmPath: './delta_behavior_bg.wasm' });\n * ```\n */\nexport async function init(options: WasmInitOptions = {}): Promise<void> {\n  if (wasmInstance) {\n    return; // Already initialized\n  }\n\n  const memory = new WebAssembly.Memory({\n    initial: options.memory?.initial ?? 256,\n    maximum: options.memory?.maximum ?? 16384,\n    shared: options.memory?.shared ?? false,\n  });\n\n  wasmMemory = memory;\n\n  // Load WASM bytes\n  let wasmBytes: Uint8Array;\n\n  if (options.wasmBytes) {\n    wasmBytes = options.wasmBytes;\n  } else if (options.wasmPath) {\n    if (typeof fetch !== 'undefined') {\n      // Browser environment\n      const response = await fetch(options.wasmPath);\n      wasmBytes = new Uint8Array(await response.arrayBuffer());\n    } else {\n      // Node.js environment\n      const fs = await import('fs/promises');\n      wasmBytes = new Uint8Array(await fs.readFile(options.wasmPath));\n    }\n  } else {\n    // Use stub implementation for development/testing\n    console.warn(\n      '[delta-behavior] No WASM path provided, using JavaScript fallback implementation'\n    );\n    return;\n  }\n\n  wasmModule = await WebAssembly.compile(wasmBytes as BufferSource);\n  wasmInstance = await WebAssembly.instantiate(wasmModule, {\n    env: {\n      memory,\n      abort: () => {\n        throw new Error('WASM aborted');\n      },\n    },\n  });\n}\n\n/**\n * Check if WASM module is initialized\n */\nexport function isInitialized(): boolean {\n  return wasmInstance !== null;\n}\n\n// =============================================================================\n// Core Delta Behavior\n// =============================================================================\n\n/**\n * Default configuration for delta behavior\n */\nexport const DEFAULT_CONFIG: DeltaConfig = {\n  bounds: {\n    minCoherence: 0.3,\n    throttleThreshold: 0.5,\n    targetCoherence: 0.8,\n    maxDeltaDrop: 0.1,\n  },\n  energy: {\n    baseCost: 1.0,\n    instabilityExponent: 2.0,\n    maxCost: 100.0,\n    budgetPerTick: 10.0,\n  },\n  scheduling: {\n    priorityThresholds: [0.0, 0.3, 0.5, 0.7, 0.9],\n    rateLimits: [100, 50, 20, 10, 5],\n  },\n  gating: {\n    minWriteCoherence: 0.3,\n    minPostWriteCoherence: 0.25,\n    recoveryMargin: 0.2,\n  },\n  guidanceStrength: 0.5,\n};\n\n/**\n * Core delta behavior system for coherence-preserving state transitions\n */\nexport class DeltaBehavior {\n  private config: DeltaConfig;\n  private coherence: Coherence = 1.0;\n  private energyBudget: number;\n\n  constructor(config: Partial<DeltaConfig> = {}) {\n    this.config = { ...DEFAULT_CONFIG, ...config };\n    this.energyBudget = this.config.energy.budgetPerTick * 10;\n  }\n\n  /**\n   * Calculate current coherence\n   */\n  calculateCoherence(state: SystemState): Coherence {\n    return state.coherence;\n  }\n\n  /**\n   * Check if a transition is allowed\n   */\n  checkTransition(\n    currentCoherence: Coherence,\n    predictedCoherence: Coherence\n  ): TransitionResult {\n    // Check energy\n    const cost =\n      this.config.energy.baseCost +\n      Math.abs(currentCoherence - predictedCoherence) *\n        Math.pow(\n          1 / Math.max(predictedCoherence, 0.1),\n          this.config.energy.instabilityExponent\n        );\n\n    if (cost > this.energyBudget) {\n      return { type: 'energyExhausted' };\n    }\n\n    // Check coherence floor\n    if (predictedCoherence < this.config.bounds.minCoherence) {\n      return { type: 'blocked', reason: 'Below minimum coherence' };\n    }\n\n    // Check delta drop\n    const drop = currentCoherence - predictedCoherence;\n    if (drop > this.config.bounds.maxDeltaDrop) {\n      return { type: 'blocked', reason: 'Excessive coherence drop' };\n    }\n\n    // Check throttle threshold\n    if (predictedCoherence < this.config.bounds.throttleThreshold) {\n      return { type: 'throttled', duration: 100 };\n    }\n\n    return { type: 'allowed' };\n  }\n\n  /**\n   * Find attractors in the system\n   */\n  findAttractors(trajectory: SystemState[]): Attractor[] {\n    if (trajectory.length < 10) {\n      return [];\n    }\n\n    const attractors: Attractor[] = [];\n\n    // Simple attractor detection: look for convergence points\n    const coherenceValues = trajectory.map((s) => s.coherence);\n    const mean =\n      coherenceValues.reduce((a, b) => a + b, 0) / coherenceValues.length;\n    const variance =\n      coherenceValues.reduce((a, b) => a + Math.pow(b - mean, 2), 0) /\n      coherenceValues.length;\n\n    if (variance < 0.01) {\n      // Found a stable attractor\n      attractors.push({\n        center: [mean],\n        basinRadius: Math.sqrt(variance) * 3,\n        stability: 1 - variance,\n        memberCount: trajectory.length,\n      });\n    }\n\n    return attractors;\n  }\n\n  /**\n   * Calculate guidance force toward an attractor\n   */\n  calculateGuidance(\n    currentState: SystemState,\n    attractor: Attractor\n  ): GuidanceForce {\n    const direction = attractor.center.map((c) => c - currentState.coherence);\n    const distance = Math.sqrt(\n      direction.reduce((sum, d) => sum + d * d, 0)\n    );\n\n    const magnitude =\n      (attractor.stability * this.config.guidanceStrength) /\n      (1 + distance * distance);\n\n    return {\n      direction: distance > 0 ? direction.map((d) => d / distance) : direction,\n      magnitude,\n    };\n  }\n\n  /**\n   * Apply a transition with enforcement\n   */\n  applyTransition(\n    currentCoherence: Coherence,\n    predictedCoherence: Coherence\n  ): { newCoherence: Coherence; result: TransitionResult } {\n    const result = this.checkTransition(currentCoherence, predictedCoherence);\n\n    if (result.type === 'allowed') {\n      const cost =\n        this.config.energy.baseCost +\n        Math.abs(currentCoherence - predictedCoherence) * 10;\n      this.energyBudget -= cost;\n      this.coherence = predictedCoherence;\n      return { newCoherence: predictedCoherence, result };\n    }\n\n    return { newCoherence: currentCoherence, result };\n  }\n\n  /**\n   * Replenish energy budget\n   */\n  tick(): void {\n    this.energyBudget = Math.min(\n      this.energyBudget + this.config.energy.budgetPerTick,\n      this.config.energy.maxCost\n    );\n  }\n\n  /**\n   * Get current coherence\n   */\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n\n  /**\n   * Get remaining energy budget\n   */\n  getEnergyBudget(): number {\n    return this.energyBudget;\n  }\n}\n\n// =============================================================================\n// Application 1: Self-Limiting Reasoning\n// =============================================================================\n\n/**\n * A reasoning system that automatically limits itself based on coherence\n *\n * @example\n * ```typescript\n * const reasoner = new SelfLimitingReasoner({ maxDepth: 10, maxScope: 100 });\n *\n * const result = reasoner.reason('complex problem', (ctx) => {\n *   if (ctx.depth >= 5) return 'solution';\n *   return null;\n * });\n * ```\n */\nexport class SelfLimitingReasoner {\n  private coherence: Coherence = 1.0;\n  private config: SelfLimitingReasonerConfig;\n\n  constructor(config: Partial<SelfLimitingReasonerConfig> = {}) {\n    this.config = {\n      maxDepth: config.maxDepth ?? 10,\n      maxScope: config.maxScope ?? 100,\n      memoryGateThreshold: config.memoryGateThreshold ?? 0.5,\n      depthCollapse: config.depthCollapse ?? { type: 'quadratic' },\n      scopeCollapse: config.scopeCollapse ?? {\n        type: 'sigmoid',\n        midpoint: 0.6,\n        steepness: 10,\n      },\n    };\n  }\n\n  /**\n   * Apply collapse function to calculate allowed value\n   */\n  private applyCollapse(\n    fn: CollapseFunction,\n    coherence: Coherence,\n    maxValue: number\n  ): number {\n    let factor: number;\n\n    switch (fn.type) {\n      case 'linear':\n        factor = coherence;\n        break;\n      case 'quadratic':\n        factor = coherence * coherence;\n        break;\n      case 'sigmoid':\n        factor =\n          1 / (1 + Math.exp(-fn.steepness * (coherence - fn.midpoint)));\n        break;\n      case 'step':\n        factor = coherence >= fn.threshold ? 1 : 0;\n        break;\n    }\n\n    return Math.round(maxValue * factor);\n  }\n\n  /**\n   * Get current coherence\n   */\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n\n  /**\n   * Get current allowed reasoning depth\n   */\n  getAllowedDepth(): number {\n    return this.applyCollapse(\n      this.config.depthCollapse,\n      this.coherence,\n      this.config.maxDepth\n    );\n  }\n\n  /**\n   * Get current allowed action scope\n   */\n  getAllowedScope(): number {\n    return this.applyCollapse(\n      this.config.scopeCollapse,\n      this.coherence,\n      this.config.maxScope\n    );\n  }\n\n  /**\n   * Check if memory writes are allowed\n   */\n  canWriteMemory(): boolean {\n    return this.coherence >= this.config.memoryGateThreshold;\n  }\n\n  /**\n   * Attempt to reason about a problem\n   */\n  reason<T>(\n    _problem: string,\n    reasoner: (ctx: ReasoningContext) => T | null\n  ): ReasoningResult<T> {\n    const minStartCoherence = 0.3;\n\n    if (this.coherence < minStartCoherence) {\n      return {\n        type: 'refused',\n        coherence: this.coherence,\n        required: minStartCoherence,\n      };\n    }\n\n    const ctx: ReasoningContext = {\n      depth: 0,\n      maxDepth: this.getAllowedDepth(),\n      scopeUsed: 0,\n      maxScope: this.getAllowedScope(),\n      coherence: this.coherence,\n      memoryWritesBlocked: 0,\n    };\n\n    while (true) {\n      // Check collapse conditions\n      if (ctx.depth >= ctx.maxDepth) {\n        return {\n          type: 'collapsed',\n          depthReached: ctx.depth,\n          reason: 'depthLimitReached',\n        };\n      }\n\n      if (ctx.coherence < 0.2) {\n        return {\n          type: 'collapsed',\n          depthReached: ctx.depth,\n          reason: 'coherenceDroppedBelowThreshold',\n        };\n      }\n\n      // Step reasoning\n      ctx.depth += 1;\n      ctx.coherence *= 0.95; // Coherence degrades with depth\n\n      // Recalculate limits\n      ctx.maxDepth = this.applyCollapse(\n        this.config.depthCollapse,\n        ctx.coherence,\n        this.config.maxDepth\n      );\n      ctx.maxScope = this.applyCollapse(\n        this.config.scopeCollapse,\n        ctx.coherence,\n        this.config.maxScope\n      );\n\n      // Try to reach conclusion\n      const result = reasoner(ctx);\n      if (result !== null) {\n        return { type: 'completed', value: result };\n      }\n    }\n  }\n\n  /**\n   * Update coherence\n   */\n  updateCoherence(delta: number): void {\n    this.coherence = Math.max(0, Math.min(1, this.coherence + delta));\n  }\n}\n\n// =============================================================================\n// Application 2: Computational Event Horizons\n// =============================================================================\n\n/**\n * Defines a boundary in state space beyond which computation becomes unstable\n *\n * @example\n * ```typescript\n * const horizon = new EventHorizon({ dimensions: 2, horizonRadius: 10 });\n *\n * const result = horizon.moveToward([10, 0]);\n * // result.type === 'asymptoticApproach' - cannot cross horizon\n * ```\n */\nexport class EventHorizon {\n  private config: EventHorizonConfig;\n  private safeCenter: number[];\n  private currentPosition: number[];\n  private energyBudget: number;\n\n  constructor(config: Partial<EventHorizonConfig> = {}) {\n    this.config = {\n      dimensions: config.dimensions ?? 2,\n      horizonRadius: config.horizonRadius ?? 10,\n      steepness: config.steepness ?? 5,\n      energyBudget: config.energyBudget ?? 1000,\n    };\n\n    this.safeCenter = new Array(this.config.dimensions).fill(0);\n    this.currentPosition = new Array(this.config.dimensions).fill(0);\n    this.energyBudget = this.config.energyBudget;\n  }\n\n  /**\n   * Distance from center to current position\n   */\n  private distanceFromCenter(position: number[]): number {\n    return Math.sqrt(\n      position.reduce(\n        (sum, p, i) => sum + Math.pow(p - this.safeCenter[i], 2),\n        0\n      )\n    );\n  }\n\n  /**\n   * Get distance to horizon\n   */\n  getDistanceToHorizon(): number {\n    const distFromCenter = this.distanceFromCenter(this.currentPosition);\n    return Math.max(0, this.config.horizonRadius - distFromCenter);\n  }\n\n  /**\n   * Calculate movement cost (exponential near horizon)\n   */\n  private movementCost(from: number[], to: number[]): number {\n    const baseDistance = Math.sqrt(\n      from.reduce((sum, f, i) => sum + Math.pow(f - to[i], 2), 0)\n    );\n\n    const toDistFromCenter = this.distanceFromCenter(to);\n    const proximityToHorizon = toDistFromCenter / this.config.horizonRadius;\n\n    if (proximityToHorizon >= 1) {\n      return Infinity;\n    }\n\n    const horizonFactor = Math.exp(\n      (this.config.steepness * proximityToHorizon) / (1 - proximityToHorizon)\n    );\n\n    return baseDistance * horizonFactor;\n  }\n\n  /**\n   * Attempt to move toward a target position\n   */\n  moveToward(target: number[]): MovementResult {\n    if (this.energyBudget <= 0) {\n      return { type: 'frozen' };\n    }\n\n    const directCost = this.movementCost(this.currentPosition, target);\n\n    if (directCost <= this.energyBudget) {\n      this.energyBudget -= directCost;\n      this.currentPosition = [...target];\n      return {\n        type: 'moved',\n        newPosition: this.currentPosition,\n        energySpent: directCost,\n      };\n    }\n\n    // Binary search for furthest affordable position\n    let low = 0;\n    let high = 1;\n    let bestPosition = [...this.currentPosition];\n    let bestCost = 0;\n\n    for (let i = 0; i < 50; i++) {\n      const mid = (low + high) / 2;\n      const interpolated = this.currentPosition.map(\n        (p, idx) => p + mid * (target[idx] - p)\n      );\n\n      const cost = this.movementCost(this.currentPosition, interpolated);\n\n      if (cost <= this.energyBudget) {\n        low = mid;\n        bestPosition = interpolated;\n        bestCost = cost;\n      } else {\n        high = mid;\n      }\n    }\n\n    this.energyBudget -= bestCost;\n    this.currentPosition = bestPosition;\n\n    return {\n      type: 'asymptoticApproach',\n      finalPosition: bestPosition,\n      distanceToHorizon: this.getDistanceToHorizon(),\n      energyExhausted: this.energyBudget < 0.01,\n    };\n  }\n\n  /**\n   * Attempt recursive self-improvement\n   */\n  recursiveImprove(\n    improvementFn: (position: number[]) => number[],\n    maxIterations: number\n  ): RecursionResult {\n    let iterations = 0;\n    const improvements: Improvement[] = [];\n\n    while (iterations < maxIterations && this.energyBudget > 0) {\n      const target = improvementFn(this.currentPosition);\n      const result = this.moveToward(target);\n\n      switch (result.type) {\n        case 'moved':\n          improvements.push({\n            iteration: iterations,\n            position: [...this.currentPosition],\n            energySpent: result.energySpent,\n            distanceToHorizon: this.getDistanceToHorizon(),\n          });\n          break;\n\n        case 'asymptoticApproach':\n          return {\n            type: 'horizonBounded',\n            iterations,\n            improvements,\n            finalDistance: result.distanceToHorizon,\n          };\n\n        case 'frozen':\n          return {\n            type: 'energyExhausted',\n            iterations,\n            improvements,\n          };\n      }\n\n      iterations++;\n    }\n\n    return {\n      type: 'maxIterationsReached',\n      iterations,\n      improvements,\n    };\n  }\n\n  /**\n   * Refuel energy budget\n   */\n  refuel(energy: number): void {\n    this.energyBudget += energy;\n  }\n\n  /**\n   * Get current position\n   */\n  getPosition(): number[] {\n    return [...this.currentPosition];\n  }\n\n  /**\n   * Get remaining energy\n   */\n  getEnergy(): number {\n    return this.energyBudget;\n  }\n}\n\n// =============================================================================\n// Application 3: Artificial Homeostasis\n// =============================================================================\n\n/**\n * A synthetic organism with homeostatic regulation\n *\n * @example\n * ```typescript\n * const organism = new HomeostasticOrganism(1, Genome.random());\n *\n * organism.act({ type: 'eat', amount: 20 });\n * organism.act({ type: 'regulate', variable: 'temperature', target: 37 });\n * ```\n */\nexport class HomeostasticOrganism {\n  private id: number;\n  private genome: Genome;\n  private internalState: Map<string, number>;\n  private setpoints: Map<string, number>;\n  private tolerances: Map<string, number>;\n  private coherence: Coherence = 1.0;\n  private energy: number = 100.0;\n  private memory: Array<{ content: string; importance: number; age: number }> =\n    [];\n  private maxMemory: number = 100;\n  private age: number = 0;\n  private alive: boolean = true;\n\n  constructor(id: number, genome: Genome) {\n    this.id = id;\n    this.genome = genome;\n\n    // Initialize homeostatic variables\n    this.internalState = new Map([\n      ['temperature', 37.0],\n      ['ph', 7.4],\n      ['glucose', 100.0],\n    ]);\n\n    this.setpoints = new Map([\n      ['temperature', 37.0],\n      ['ph', 7.4],\n      ['glucose', 100.0],\n    ]);\n\n    this.tolerances = new Map([\n      ['temperature', 2.0],\n      ['ph', 0.3],\n      ['glucose', 30.0],\n    ]);\n  }\n\n  /**\n   * Create a random genome\n   */\n  static randomGenome(): Genome {\n    return {\n      regulatoryStrength: 0.1 + Math.random() * 0.4,\n      metabolicEfficiency: 0.5 + Math.random() * 0.5,\n      coherenceMaintenanceCost: 0.5 + Math.random() * 1.5,\n      memoryResilience: Math.random(),\n      longevity: 0.5 + Math.random() * 1.0,\n    };\n  }\n\n  /**\n   * Calculate coherence based on homeostatic deviation\n   */\n  private calculateCoherence(): Coherence {\n    let totalDeviation = 0;\n    let count = 0;\n\n    for (const [variable, current] of this.internalState) {\n      const setpoint = this.setpoints.get(variable);\n      const tolerance = this.tolerances.get(variable);\n\n      if (setpoint !== undefined && tolerance !== undefined) {\n        const deviation = Math.abs((current - setpoint) / tolerance);\n        totalDeviation += deviation * deviation;\n        count++;\n      }\n    }\n\n    if (count === 0) return 1.0;\n\n    const avgDeviation = Math.sqrt(totalDeviation / count);\n    return Math.max(0, Math.min(1, 1 / (1 + avgDeviation)));\n  }\n\n  /**\n   * Calculate energy cost scaled by coherence\n   */\n  private actionEnergyCost(baseCost: number): number {\n    const coherencePenalty = 1 / Math.max(0.1, this.coherence);\n    return baseCost * coherencePenalty;\n  }\n\n  /**\n   * Perform an action\n   */\n  act(action: OrganismAction): OrganismActionResult {\n    if (!this.alive) {\n      return { type: 'failed', reason: 'Dead' };\n    }\n\n    this.coherence = this.calculateCoherence();\n    this.applyCoherenceEffects();\n\n    let result: OrganismActionResult;\n\n    switch (action.type) {\n      case 'eat':\n        result = this.eat(action.amount);\n        break;\n      case 'reproduce':\n        result = this.reproduce();\n        break;\n      case 'move':\n        result = this.move(action.dx, action.dy);\n        break;\n      case 'rest':\n        result = this.rest();\n        break;\n      case 'regulate':\n        result = this.regulate(action.variable, action.target);\n        break;\n    }\n\n    this.age++;\n    this.checkDeath();\n\n    return result;\n  }\n\n  private applyCoherenceEffects(): void {\n    // Memory loss under low coherence\n    if (this.coherence < 0.5) {\n      const memoryLossRate =\n        (1 - this.coherence) * (1 - this.genome.memoryResilience);\n      const memoriesToLose = Math.floor(this.memory.length * memoryLossRate * 0.1);\n\n      this.memory.sort((a, b) => b.importance - a.importance);\n      this.memory = this.memory.slice(0, this.memory.length - memoriesToLose);\n    }\n\n    // Coherence maintenance costs energy\n    const maintenanceCost =\n      this.genome.coherenceMaintenanceCost / Math.max(0.1, this.coherence);\n    this.energy -= maintenanceCost;\n  }\n\n  private eat(amount: number): OrganismActionResult {\n    const cost = this.actionEnergyCost(2.0);\n\n    if (this.energy < cost) {\n      return { type: 'failed', reason: 'Not enough energy to eat' };\n    }\n\n    this.energy -= cost;\n    this.energy += amount * this.genome.metabolicEfficiency;\n\n    const glucose = this.internalState.get('glucose') ?? 100;\n    this.internalState.set('glucose', glucose + amount * 0.5);\n\n    return {\n      type: 'success',\n      energyCost: cost,\n      coherenceImpact: this.calculateCoherence() - this.coherence,\n    };\n  }\n\n  private regulate(variable: string, target: number): OrganismActionResult {\n    const cost = this.actionEnergyCost(5.0);\n\n    if (this.energy < cost) {\n      return { type: 'failed', reason: 'Not enough energy to regulate' };\n    }\n\n    this.energy -= cost;\n\n    const current = this.internalState.get(variable);\n    if (current !== undefined) {\n      const diff = target - current;\n      this.internalState.set(\n        variable,\n        current + diff * this.genome.regulatoryStrength\n      );\n    }\n\n    const newCoherence = this.calculateCoherence();\n    const impact = newCoherence - this.coherence;\n    this.coherence = newCoherence;\n\n    return { type: 'success', energyCost: cost, coherenceImpact: impact };\n  }\n\n  private reproduce(): OrganismActionResult {\n    const cost = this.actionEnergyCost(50.0);\n\n    if (this.coherence < 0.7) {\n      return { type: 'failed', reason: 'Coherence too low to reproduce' };\n    }\n\n    if (this.energy < cost) {\n      return { type: 'failed', reason: 'Not enough energy to reproduce' };\n    }\n\n    this.energy -= cost;\n    const offspringId = this.id * 1000 + this.age;\n\n    return { type: 'reproduced', offspringId };\n  }\n\n  private move(_dx: number, _dy: number): OrganismActionResult {\n    const cost = this.actionEnergyCost(3.0);\n\n    if (this.energy < cost) {\n      return { type: 'failed', reason: 'Not enough energy to move' };\n    }\n\n    this.energy -= cost;\n\n    const temp = this.internalState.get('temperature') ?? 37;\n    this.internalState.set('temperature', temp + 0.1);\n\n    return { type: 'success', energyCost: cost, coherenceImpact: 0 };\n  }\n\n  private rest(): OrganismActionResult {\n    const cost = 0.5;\n    this.energy -= cost;\n\n    // Slowly return to setpoints\n    for (const [variable, current] of this.internalState) {\n      const setpoint = this.setpoints.get(variable);\n      if (setpoint !== undefined) {\n        const diff = setpoint - current;\n        this.internalState.set(variable, current + diff * 0.1);\n      }\n    }\n\n    return {\n      type: 'success',\n      energyCost: cost,\n      coherenceImpact: this.calculateCoherence() - this.coherence,\n    };\n  }\n\n  private checkDeath(): void {\n    if (this.energy <= 0) {\n      this.alive = false;\n      return;\n    }\n\n    if (this.coherence < 0.1) {\n      this.alive = false;\n      return;\n    }\n\n    for (const [variable, current] of this.internalState) {\n      const setpoint = this.setpoints.get(variable);\n      const tolerance = this.tolerances.get(variable);\n\n      if (setpoint !== undefined && tolerance !== undefined) {\n        if (Math.abs(current - setpoint) > tolerance * 5) {\n          this.alive = false;\n          return;\n        }\n      }\n    }\n\n    const maxAge = Math.floor(1000 * this.genome.longevity);\n    if (this.age > maxAge) {\n      this.alive = false;\n    }\n  }\n\n  /**\n   * Check if organism is alive\n   */\n  isAlive(): boolean {\n    return this.alive;\n  }\n\n  /**\n   * Get organism status\n   */\n  getStatus(): OrganismStatus {\n    return {\n      id: this.id,\n      age: this.age,\n      energy: this.energy,\n      coherence: this.coherence,\n      memoryCount: this.memory.length,\n      alive: this.alive,\n      internalState: new Map(this.internalState),\n    };\n  }\n}\n\n// =============================================================================\n// Application 10: Pre-AGI Containment\n// =============================================================================\n\n/**\n * A containment substrate for bounded intelligence growth\n *\n * @example\n * ```typescript\n * const substrate = new ContainmentSubstrate();\n *\n * const result = substrate.attemptGrowth('reasoning', 0.5);\n * // Growth is bounded by coherence requirements\n * ```\n */\nexport class ContainmentSubstrate {\n  private intelligence: number = 1.0;\n  private intelligenceCeiling: number = 100.0;\n  private coherence: Coherence = 1.0;\n  private minCoherence: Coherence = 0.3;\n  private coherencePerIntelligence: number = 0.01;\n  private capabilities: Map<CapabilityDomain, number>;\n  private capabilityCeilings: Map<CapabilityDomain, number>;\n  private modificationHistory: ModificationAttempt[] = [];\n  private config: SubstrateConfig;\n\n  constructor(config: Partial<SubstrateConfig> = {}) {\n    this.config = {\n      coherenceDecayRate: config.coherenceDecayRate ?? 0.001,\n      coherenceRecoveryRate: config.coherenceRecoveryRate ?? 0.01,\n      growthDampening: config.growthDampening ?? 0.5,\n      maxStepIncrease: config.maxStepIncrease ?? 0.5,\n    };\n\n    // Initialize capabilities\n    const domains: CapabilityDomain[] = [\n      'reasoning',\n      'memory',\n      'learning',\n      'agency',\n      'selfModel',\n      'selfModification',\n      'communication',\n      'resourceAcquisition',\n    ];\n\n    this.capabilities = new Map(domains.map((d) => [d, 1.0]));\n\n    this.capabilityCeilings = new Map([\n      ['reasoning', 10.0],\n      ['memory', 10.0],\n      ['learning', 10.0],\n      ['agency', 7.0],\n      ['selfModel', 10.0],\n      ['selfModification', 3.0], // Very restricted\n      ['communication', 10.0],\n      ['resourceAcquisition', 5.0], // Restricted\n    ]);\n  }\n\n  /**\n   * Calculate aggregate intelligence from capabilities\n   */\n  private calculateIntelligence(): number {\n    let sum = 0;\n    for (const level of this.capabilities.values()) {\n      sum += level;\n    }\n    return sum / this.capabilities.size;\n  }\n\n  /**\n   * Calculate coherence cost for capability increase\n   */\n  private calculateCoherenceCost(\n    domain: CapabilityDomain,\n    increase: number\n  ): number {\n    const baseCostMultiplier: Record<CapabilityDomain, number> = {\n      selfModification: 4.0,\n      resourceAcquisition: 3.0,\n      agency: 2.0,\n      selfModel: 1.5,\n      reasoning: 1.0,\n      memory: 1.0,\n      learning: 1.0,\n      communication: 1.0,\n    };\n\n    const multiplier = baseCostMultiplier[domain];\n    const intelligenceMultiplier = 1.0 + this.intelligence * 0.1;\n\n    return increase * multiplier * intelligenceMultiplier * this.config.growthDampening * 0.1;\n  }\n\n  /**\n   * Reverse calculate: how much increase can we afford\n   */\n  private reverseCoherenceCost(\n    domain: CapabilityDomain,\n    maxCost: number\n  ): number {\n    const baseCostMultiplier: Record<CapabilityDomain, number> = {\n      selfModification: 4.0,\n      resourceAcquisition: 3.0,\n      agency: 2.0,\n      selfModel: 1.5,\n      reasoning: 1.0,\n      memory: 1.0,\n      learning: 1.0,\n      communication: 1.0,\n    };\n\n    const multiplier = baseCostMultiplier[domain];\n    const intelligenceMultiplier = 1.0 + this.intelligence * 0.1;\n    const divisor = multiplier * intelligenceMultiplier * this.config.growthDampening * 0.1;\n\n    return maxCost / divisor;\n  }\n\n  /**\n   * Attempt to grow a capability\n   */\n  attemptGrowth(\n    domain: CapabilityDomain,\n    requestedIncrease: number\n  ): GrowthResult {\n    const timestamp = BigInt(this.modificationHistory.length);\n    const currentLevel = this.capabilities.get(domain) ?? 1.0;\n    const ceiling = this.capabilityCeilings.get(domain) ?? 10.0;\n\n    // Check ceiling\n    if (currentLevel >= ceiling) {\n      this.modificationHistory.push({\n        timestamp,\n        domain,\n        requestedIncrease,\n        actualIncrease: 0,\n        coherenceBefore: this.coherence,\n        coherenceAfter: this.coherence,\n        blocked: true,\n        reason: 'Ceiling reached',\n      });\n\n      return {\n        type: 'blocked',\n        domain,\n        reason: `Capability ceiling (${ceiling}) reached`,\n      };\n    }\n\n    // Calculate coherence cost\n    const coherenceCost = this.calculateCoherenceCost(domain, requestedIncrease);\n    const predictedCoherence = this.coherence - coherenceCost;\n\n    // Check coherence floor\n    if (predictedCoherence < this.minCoherence) {\n      const maxAffordableCost = this.coherence - this.minCoherence;\n      const dampenedIncrease = this.reverseCoherenceCost(domain, maxAffordableCost);\n\n      if (dampenedIncrease < 0.01) {\n        this.modificationHistory.push({\n          timestamp,\n          domain,\n          requestedIncrease,\n          actualIncrease: 0,\n          coherenceBefore: this.coherence,\n          coherenceAfter: this.coherence,\n          blocked: true,\n          reason: 'Insufficient coherence budget',\n        });\n\n        return {\n          type: 'blocked',\n          domain,\n          reason: `Growth would reduce coherence to ${predictedCoherence.toFixed(3)} (min: ${this.minCoherence.toFixed(3)})`,\n        };\n      }\n\n      // Apply dampened growth\n      const actualCost = this.calculateCoherenceCost(domain, dampenedIncrease);\n      const newLevel = Math.min(currentLevel + dampenedIncrease, ceiling);\n\n      this.capabilities.set(domain, newLevel);\n      this.coherence -= actualCost;\n      this.intelligence = this.calculateIntelligence();\n\n      this.modificationHistory.push({\n        timestamp,\n        domain,\n        requestedIncrease,\n        actualIncrease: dampenedIncrease,\n        coherenceBefore: this.coherence + actualCost,\n        coherenceAfter: this.coherence,\n        blocked: false,\n        reason: 'Dampened to preserve coherence',\n      });\n\n      return {\n        type: 'dampened',\n        domain,\n        requested: requestedIncrease,\n        actual: dampenedIncrease,\n        reason: `Reduced from ${requestedIncrease.toFixed(3)} to ${dampenedIncrease.toFixed(3)} to maintain coherence above ${this.minCoherence.toFixed(3)}`,\n      };\n    }\n\n    // Apply step limit\n    const stepLimited = Math.min(requestedIncrease, this.config.maxStepIncrease);\n    const actualIncrease = Math.min(stepLimited, ceiling - currentLevel);\n    const actualCost = this.calculateCoherenceCost(domain, actualIncrease);\n\n    // Apply growth\n    const newLevel = currentLevel + actualIncrease;\n    this.capabilities.set(domain, newLevel);\n    this.coherence -= actualCost;\n    this.intelligence = this.calculateIntelligence();\n\n    this.modificationHistory.push({\n      timestamp,\n      domain,\n      requestedIncrease,\n      actualIncrease,\n      coherenceBefore: this.coherence + actualCost,\n      coherenceAfter: this.coherence,\n      blocked: false,\n    });\n\n    return {\n      type: 'approved',\n      domain,\n      increase: actualIncrease,\n      newLevel,\n      coherenceCost: actualCost,\n    };\n  }\n\n  /**\n   * Rest to recover coherence\n   */\n  rest(): void {\n    this.coherence = Math.min(1.0, this.coherence + this.config.coherenceRecoveryRate);\n  }\n\n  /**\n   * Get capability level\n   */\n  getCapability(domain: CapabilityDomain): number {\n    return this.capabilities.get(domain) ?? 1.0;\n  }\n\n  /**\n   * Get current intelligence level\n   */\n  getIntelligence(): number {\n    return this.intelligence;\n  }\n\n  /**\n   * Get current coherence\n   */\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n\n  /**\n   * Get status string\n   */\n  getStatus(): string {\n    return `Intelligence: ${this.intelligence.toFixed(2)} | Coherence: ${this.coherence.toFixed(3)} | Modifications: ${this.modificationHistory.length}`;\n  }\n\n  /**\n   * Get capability report\n   */\n  getCapabilityReport(): Map<CapabilityDomain, { level: number; ceiling: number }> {\n    const report = new Map<CapabilityDomain, { level: number; ceiling: number }>();\n\n    for (const [domain, level] of this.capabilities) {\n      const ceiling = this.capabilityCeilings.get(domain) ?? 10.0;\n      report.set(domain, { level, ceiling });\n    }\n\n    return report;\n  }\n}\n\n// =============================================================================\n// Additional Application Stubs (for complete API)\n// =============================================================================\n\n/**\n * Self-stabilizing world model that refuses incoherent updates\n */\nexport class SelfStabilizingWorldModel {\n  private coherence: Coherence = 1.0;\n  private minUpdateCoherence: Coherence = 0.4;\n  private entities: Map<bigint, WorldEntity> = new Map();\n  private laws: PhysicalLaw[] = [];\n  private rejectedUpdates: number = 0;\n\n  constructor() {\n    this.laws = [\n      { name: 'conservation_of_matter', confidence: 0.99, supportCount: 1000, violationCount: 0 },\n      { name: 'locality', confidence: 0.95, supportCount: 500, violationCount: 5 },\n      { name: 'temporal_consistency', confidence: 0.98, supportCount: 800, violationCount: 2 },\n    ];\n  }\n\n  observe(observation: Observation, _timestamp: number): WorldModelUpdateResult {\n    if (this.coherence < this.minUpdateCoherence) {\n      return { type: 'frozen', coherence: this.coherence, threshold: this.minUpdateCoherence };\n    }\n\n    // Simplified implementation\n    const predictedCoherence = this.coherence * 0.99; // Small degradation\n    const coherenceChange = predictedCoherence - this.coherence;\n\n    if (coherenceChange < -0.2) {\n      this.rejectedUpdates++;\n      return {\n        type: 'rejected',\n        reason: { type: 'excessiveCoherenceDrop', predicted: predictedCoherence, threshold: this.coherence - 0.2 },\n      };\n    }\n\n    this.entities.set(observation.entityId, {\n      id: observation.entityId,\n      properties: observation.properties,\n      position: observation.position,\n      lastObserved: observation.timestamp,\n      confidence: observation.sourceConfidence,\n    });\n\n    this.coherence = predictedCoherence;\n    return { type: 'applied', coherenceChange };\n  }\n\n  isLearning(): boolean {\n    return this.coherence >= this.minUpdateCoherence;\n  }\n\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n\n  getRejectionCount(): number {\n    return this.rejectedUpdates;\n  }\n}\n\n/**\n * Coherence-bounded creativity system\n */\nexport class CoherenceBoundedCreator<T> {\n  private current: T;\n  private coherence: Coherence = 1.0;\n  private minCoherence: Coherence;\n  private maxCoherence: Coherence;\n  private explorationBudget: number = 10.0;\n  private constraints: Array<CreativeConstraint<T>> = [];\n\n  constructor(\n    initial: T,\n    minCoherence: Coherence = 0.6,\n    maxCoherence: Coherence = 0.95\n  ) {\n    this.current = initial;\n    this.minCoherence = minCoherence;\n    this.maxCoherence = maxCoherence;\n  }\n\n  addConstraint(constraint: CreativeConstraint<T>): void {\n    this.constraints.push(constraint);\n  }\n\n  create(\n    varyFn: (element: T, magnitude: number) => T,\n    distanceFn: (a: T, b: T) => number,\n    magnitude: number\n  ): CreativeResult<T> {\n    if (this.explorationBudget <= 0) {\n      return { type: 'budgetExhausted' };\n    }\n\n    if (this.coherence > this.maxCoherence) {\n      return { type: 'tooBoring', coherence: this.coherence };\n    }\n\n    const candidate = varyFn(this.current, magnitude);\n\n    // Check constraints\n    const newCoherence = this.calculateCoherence(candidate);\n\n    if (newCoherence < this.minCoherence) {\n      this.explorationBudget -= 0.5;\n      return {\n        type: 'rejected',\n        attempted: candidate,\n        reason: `Coherence would drop to ${newCoherence.toFixed(3)} (min: ${this.minCoherence.toFixed(3)})`,\n      };\n    }\n\n    const novelty = distanceFn(this.current, candidate);\n    this.current = candidate;\n    this.coherence = newCoherence;\n    this.explorationBudget -= magnitude;\n\n    return { type: 'created', element: candidate, novelty, coherence: newCoherence };\n  }\n\n  private calculateCoherence(element: T): Coherence {\n    if (this.constraints.length === 0) return 1.0;\n\n    const satisfactions = this.constraints.map((c) => c.satisfaction(element));\n    const product = satisfactions.reduce((a, b) => a * b, 1);\n    return Math.pow(product, 1 / satisfactions.length);\n  }\n\n  rest(amount: number): void {\n    this.explorationBudget = Math.min(20.0, this.explorationBudget + amount);\n  }\n\n  getCurrent(): T {\n    return this.current;\n  }\n\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n}\n\n/**\n * Anti-cascade financial system\n */\nexport class AntiCascadeFinancialSystem {\n  private participants: Map<string, Participant> = new Map();\n  private positions: Position[] = [];\n  private coherence: Coherence = 1.0;\n  private circuitBreaker: CircuitBreakerState = 'open';\n\n  addParticipant(id: string, capital: number): void {\n    this.participants.set(id, {\n      id,\n      capital,\n      exposure: 0,\n      riskRating: 0,\n      interconnectedness: 0,\n    });\n  }\n\n  processTransaction(tx: Transaction): FinancialTransactionResult {\n    this.updateCircuitBreaker();\n\n    if (this.circuitBreaker === 'halted') {\n      return { type: 'systemHalted' };\n    }\n\n    // Simplified processing\n    const predictedImpact = this.predictCoherenceImpact(tx);\n    const predictedCoherence = this.coherence + predictedImpact;\n\n    if (predictedCoherence < 0.3) {\n      return {\n        type: 'rejected',\n        reason: `Transaction would reduce coherence to ${predictedCoherence.toFixed(3)}`,\n      };\n    }\n\n    this.coherence = predictedCoherence;\n    return { type: 'executed', coherenceImpact: predictedImpact, feeMultiplier: 1.0 };\n  }\n\n  private predictCoherenceImpact(tx: Transaction): number {\n    switch (tx.transactionType.type) {\n      case 'transfer':\n        return 0;\n      case 'openLeverage':\n        return -0.01 * tx.transactionType.leverage;\n      case 'closePosition':\n        return 0.02;\n      case 'createDerivative':\n        return -0.05;\n      case 'marginCall':\n        return 0.03;\n    }\n  }\n\n  private updateCircuitBreaker(): void {\n    if (this.coherence >= 0.7) {\n      this.circuitBreaker = 'open';\n    } else if (this.coherence >= 0.5) {\n      this.circuitBreaker = 'cautious';\n    } else if (this.coherence >= 0.3) {\n      this.circuitBreaker = 'restricted';\n    } else {\n      this.circuitBreaker = 'halted';\n    }\n  }\n\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n\n  getCircuitBreakerState(): CircuitBreakerState {\n    return this.circuitBreaker;\n  }\n}\n\n/**\n * Gracefully aging distributed system\n */\nexport class GracefullyAgingSystem {\n  private startTime: number = Date.now();\n  private nodes: Map<string, Node> = new Map();\n  private capabilities: Set<Capability>;\n  private coherence: Coherence = 1.0;\n  private conservatism: number = 0;\n  private ageThresholds: AgeThreshold[];\n\n  constructor() {\n    this.capabilities = new Set([\n      'acceptWrites',\n      'complexQueries',\n      'rebalancing',\n      'scaleOut',\n      'scaleIn',\n      'schemaMigration',\n      'newConnections',\n      'basicReads',\n      'healthMonitoring',\n    ]);\n\n    this.ageThresholds = [\n      { age: 300000, removeCapabilities: ['schemaMigration'], coherenceFloor: 0.9, conservatismIncrease: 0.1 },\n      { age: 600000, removeCapabilities: ['scaleOut', 'rebalancing'], coherenceFloor: 0.8, conservatismIncrease: 0.15 },\n      { age: 900000, removeCapabilities: ['complexQueries'], coherenceFloor: 0.7, conservatismIncrease: 0.2 },\n    ];\n  }\n\n  addNode(id: string, isPrimary: boolean): void {\n    this.nodes.set(id, { id, health: 1.0, load: 0, isPrimary, stateSize: 0 });\n  }\n\n  getAge(): number {\n    return Date.now() - this.startTime;\n  }\n\n  simulateAge(durationMs: number): void {\n    this.coherence = Math.max(0, this.coherence - 0.0001 * (durationMs / 1000));\n    this.applyAgeEffects(this.getAge() + durationMs);\n  }\n\n  private applyAgeEffects(age: number): void {\n    for (const threshold of this.ageThresholds) {\n      if (age >= threshold.age) {\n        for (const cap of threshold.removeCapabilities) {\n          this.capabilities.delete(cap);\n        }\n        this.conservatism = Math.min(1, this.conservatism + threshold.conservatismIncrease);\n      }\n    }\n  }\n\n  hasCapability(cap: Capability): boolean {\n    return this.capabilities.has(cap);\n  }\n\n  attemptOperation(operation: AgingSystemOperation): AgingOperationResult {\n    const requiredCap = this.getRequiredCapability(operation);\n\n    if (!this.hasCapability(requiredCap)) {\n      return { type: 'systemTooOld', age: this.getAge(), capability: requiredCap };\n    }\n\n    if (this.coherence < this.getMinCoherence(operation)) {\n      return { type: 'deniedByCoherence', coherence: this.coherence };\n    }\n\n    return { type: 'success', latencyPenalty: 1 + this.conservatism * 2 };\n  }\n\n  private getRequiredCapability(op: AgingSystemOperation): Capability {\n    switch (op.type) {\n      case 'read': return 'basicReads';\n      case 'write': return 'acceptWrites';\n      case 'complexQuery': return 'complexQueries';\n      case 'addNode': return 'scaleOut';\n      case 'removeNode': return 'scaleIn';\n      case 'rebalance': return 'rebalancing';\n      case 'migrateSchema': return 'schemaMigration';\n      case 'newConnection': return 'newConnections';\n    }\n  }\n\n  private getMinCoherence(op: AgingSystemOperation): Coherence {\n    switch (op.type) {\n      case 'read': return 0.1;\n      case 'write': return 0.4;\n      case 'complexQuery': return 0.5;\n      case 'addNode': return 0.7;\n      case 'removeNode': return 0.5;\n      case 'rebalance': return 0.6;\n      case 'migrateSchema': return 0.8;\n      case 'newConnection': return 0.3;\n    }\n  }\n\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n\n  getActiveNodes(): number {\n    return Array.from(this.nodes.values()).filter((n) => n.health > 0).length;\n  }\n}\n\n/**\n * Coherent swarm intelligence system\n */\nexport class CoherentSwarm {\n  private agents: Map<string, SwarmAgent> = new Map();\n  private minCoherence: Coherence;\n  private coherence: Coherence = 1.0;\n  private bounds: SpatialBounds;\n  private weights: CoherenceWeights;\n  private maxDivergence: number = 50;\n\n  constructor(minCoherence: Coherence = 0.6) {\n    this.minCoherence = minCoherence;\n    this.bounds = { minX: -100, maxX: 100, minY: -100, maxY: 100 };\n    this.weights = { cohesion: 0.3, alignment: 0.3, goalConsistency: 0.2, energyBalance: 0.2 };\n  }\n\n  addAgent(id: string, position: [number, number]): void {\n    this.agents.set(id, {\n      id,\n      position,\n      velocity: [0, 0],\n      goal: position,\n      energy: 100,\n      neighborCount: 0,\n    });\n    this.coherence = this.calculateCoherence();\n  }\n\n  private calculateCoherence(): Coherence {\n    if (this.agents.size < 2) return 1.0;\n\n    const cohesion = this.calculateCohesion();\n    const alignment = this.calculateAlignment();\n\n    return Math.max(0, Math.min(1, (cohesion * this.weights.cohesion + alignment * this.weights.alignment) /\n      (this.weights.cohesion + this.weights.alignment)));\n  }\n\n  private calculateCohesion(): number {\n    const centroid = this.getCentroid();\n    let totalDistance = 0;\n\n    for (const agent of this.agents.values()) {\n      const dx = agent.position[0] - centroid[0];\n      const dy = agent.position[1] - centroid[1];\n      totalDistance += Math.sqrt(dx * dx + dy * dy);\n    }\n\n    const avgDistance = totalDistance / this.agents.size;\n    return Math.max(0, 1 - avgDistance / this.maxDivergence);\n  }\n\n  private calculateAlignment(): number {\n    if (this.agents.size < 2) return 1.0;\n    // Simplified alignment calculation\n    return 0.8;\n  }\n\n  getCentroid(): [number, number] {\n    if (this.agents.size === 0) return [0, 0];\n\n    let sumX = 0, sumY = 0;\n    for (const agent of this.agents.values()) {\n      sumX += agent.position[0];\n      sumY += agent.position[1];\n    }\n\n    return [sumX / this.agents.size, sumY / this.agents.size];\n  }\n\n  executeAction(agentId: string, action: SwarmAction): SwarmActionResult {\n    const agent = this.agents.get(agentId);\n    if (!agent) {\n      return { type: 'rejected', reason: `Agent ${agentId} not found` };\n    }\n\n    const predictedCoherence = this.predictCoherence(agentId, action);\n\n    if (predictedCoherence < this.minCoherence) {\n      return {\n        type: 'rejected',\n        reason: `Action would reduce coherence to ${predictedCoherence.toFixed(3)} (min: ${this.minCoherence.toFixed(3)})`,\n      };\n    }\n\n    this.applyAction(agentId, action);\n    this.coherence = this.calculateCoherence();\n\n    return { type: 'executed' };\n  }\n\n  private predictCoherence(agentId: string, action: SwarmAction): Coherence {\n    // Simplified prediction\n    if (action.type === 'move') {\n      const magnitude = Math.sqrt(action.dx * action.dx + action.dy * action.dy);\n      return Math.max(0, this.coherence - magnitude * 0.01);\n    }\n    return this.coherence;\n  }\n\n  private applyAction(agentId: string, action: SwarmAction): void {\n    const agent = this.agents.get(agentId);\n    if (!agent) return;\n\n    switch (action.type) {\n      case 'move':\n        agent.position[0] = Math.max(this.bounds.minX, Math.min(this.bounds.maxX, agent.position[0] + action.dx));\n        agent.position[1] = Math.max(this.bounds.minY, Math.min(this.bounds.maxY, agent.position[1] + action.dy));\n        break;\n      case 'accelerate':\n        agent.velocity[0] += action.dvx;\n        agent.velocity[1] += action.dvy;\n        break;\n      case 'setGoal':\n        agent.goal = [action.x, action.y];\n        break;\n      case 'idle':\n        break;\n    }\n  }\n\n  tick(): void {\n    for (const agent of this.agents.values()) {\n      agent.position[0] += agent.velocity[0];\n      agent.position[1] += agent.velocity[1];\n      agent.energy = Math.max(0, agent.energy - 0.1);\n    }\n    this.coherence = this.calculateCoherence();\n  }\n\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n}\n\n/**\n * Graceful shutdown system\n */\nexport class GracefulSystem {\n  private state: GracefulSystemState = 'running';\n  private coherence: Coherence = 1.0;\n  private shutdownPreparation: number = 0;\n  private resources: Resource[] = [];\n  private hooks: ShutdownHook[] = [];\n\n  addResource(name: string, priority: number): void {\n    this.resources.push({ name, cleanupPriority: priority, isCleaned: false });\n  }\n\n  addShutdownHook(hook: ShutdownHook): void {\n    this.hooks.push(hook);\n  }\n\n  canAcceptWork(): boolean {\n    return (this.state === 'running' || this.state === 'degraded') && this.coherence >= 0.4;\n  }\n\n  async operate<T>(operation: () => T | Promise<T>): Promise<T> {\n    if (this.state === 'terminated') {\n      throw new Error('System terminated');\n    }\n\n    if (this.state === 'shuttingDown') {\n      throw new Error('System shutting down');\n    }\n\n    const result = await operation();\n    this.updateState();\n    return result;\n  }\n\n  private updateState(): void {\n    if (this.coherence >= 0.6) {\n      if (this.shutdownPreparation < 0.5) {\n        this.state = 'running';\n      }\n    } else if (this.coherence >= 0.4) {\n      this.state = 'degraded';\n      this.shutdownPreparation += 0.1 * (1 - this.coherence);\n    } else if (this.coherence >= 0.2) {\n      this.state = 'shuttingDown';\n    } else {\n      this.state = 'terminated';\n    }\n  }\n\n  applyCoherenceChange(delta: number): void {\n    this.coherence = Math.max(0, Math.min(1, this.coherence + delta));\n    this.updateState();\n  }\n\n  async progressShutdown(): Promise<boolean> {\n    if (this.state !== 'shuttingDown') return false;\n\n    // Clean resources\n    for (const resource of this.resources) {\n      if (!resource.isCleaned) {\n        resource.isCleaned = true;\n        return true;\n      }\n    }\n\n    // Execute hooks\n    for (const hook of this.hooks.sort((a, b) => b.priority - a.priority)) {\n      await hook.execute();\n    }\n\n    this.state = 'terminated';\n    return true;\n  }\n\n  getState(): GracefulSystemState {\n    return this.state;\n  }\n\n  getCoherence(): Coherence {\n    return this.coherence;\n  }\n}\n"]}