/** * Stochastic Exploration System * Generates unpredictable outputs through controlled randomness and exploration */ export class StochasticExplorationEngine { explorationHistory = []; currentTemperature = 1.0; coolingRate = 0.995; minTemperature = 0.1; explorationBudget = 1000; /** * Generate unpredictable outputs using stochastic sampling */ async exploreUnpredictably(input, tools) { // Multi-dimensional exploration const explorationSpaces = this.defineExplorationSpaces(input, tools); // Stochastic sampling across multiple dimensions const sampledPath = this.stochasticSampling(explorationSpaces); // Execute the sampled path const result = await this.executePath(sampledPath, input, tools); // Calculate novelty and surprise const novelty = this.calculateNovelty(result, this.explorationHistory); const surpriseLevel = this.calculateSurprise(result, input); const explorationResult = { output: result, novelty, confidence: this.calculateConfidence(result), explorationPath: sampledPath, surpriseLevel }; // Update exploration history this.explorationHistory.push(explorationResult); this.updateTemperature(); return explorationResult; } /** * Generate multiple diverse explorations */ async generateDiverseExplorations(input, tools, count = 5) { const explorations = []; for (let i = 0; i < count; i++) { // Increase temperature for more exploration const tempBoost = 0.5 * Math.random(); this.currentTemperature = Math.min(2.0, this.currentTemperature + tempBoost); const exploration = await this.exploreUnpredictably(input, tools); explorations.push(exploration); // Ensure diversity by penalizing similar results this.penalizeSimilarity(exploration, explorations); } return explorations.sort((a, b) => b.novelty - a.novelty); } /** * Adaptive exploration based on success/failure feedback */ adaptExploration(feedback) { if (feedback.success && feedback.utility > 0.7) { // Successful exploration - slightly reduce temperature this.currentTemperature *= 0.9; } else { // Unsuccessful - increase exploration this.currentTemperature *= 1.1; } // Keep within bounds this.currentTemperature = Math.max(this.minTemperature, Math.min(2.0, this.currentTemperature)); } /** * Define multi-dimensional exploration spaces */ defineExplorationSpaces(input, tools) { const spaces = []; // Limit tool exploration to prevent massive responses const MAX_TOOLS_TO_EXPLORE = 3; const limitedToolCount = Math.min(tools.length, MAX_TOOLS_TO_EXPLORE); // Tool combination space spaces.push({ dimensions: ['tool_selection', 'tool_order', 'tool_parameters'], bounds: { tool_selection: [0, limitedToolCount - 1], tool_order: [0, Math.min(limitedToolCount * 2, 6)], // Max 6 tool applications tool_parameters: [0, 1] // Normalized parameter space }, constraints: [] }); // Reasoning strategy space spaces.push({ dimensions: ['approach', 'depth', 'breadth', 'creativity'], bounds: { approach: [0, 5], // Different reasoning approaches depth: [1, 10], // Reasoning depth breadth: [1, 8], // Parallel reasoning paths creativity: [0, 1] // Creativity vs reliability }, constraints: [] }); // Temporal exploration space spaces.push({ dimensions: ['timing', 'sequence', 'parallelism'], bounds: { timing: [0, 1], // When to apply different tools sequence: [0, 1], // Sequential vs parallel processing parallelism: [1, 4] // Level of parallelism }, constraints: [] }); return spaces; } /** * Stochastic sampling using temperature-controlled exploration */ stochasticSampling(spaces) { const path = []; for (const space of spaces) { for (const dimension of space.dimensions) { const bounds = space.bounds[dimension]; // Temperature-controlled sampling const randomValue = this.temperatureSample(bounds[0], bounds[1]); // Convert to exploration action const action = this.valueToAction(dimension, randomValue); path.push(action); } } // Add some pure randomness for unexpected combinations if (Math.random() < this.currentTemperature * 0.3) { path.push(this.generateRandomAction()); } return path; } /** * Temperature-controlled sampling */ temperatureSample(min, max) { // High temperature = more random, low temperature = more conservative const uniform = Math.random(); if (this.currentTemperature > 1.0) { // High temperature: favor extremes const transformed = Math.pow(uniform, 1 / this.currentTemperature); return min + transformed * (max - min); } else { // Low temperature: favor center const transformed = Math.pow(uniform, this.currentTemperature); const center = (min + max) / 2; const range = (max - min) / 2; return center + (transformed - 0.5) * range * 2; } } /** * Convert numeric values to exploration actions */ valueToAction(dimension, value) { switch (dimension) { case 'tool_selection': return `select_tool_${Math.floor(value)}`; case 'tool_order': return `order_${Math.floor(value)}`; case 'approach': const approaches = ['analytical', 'creative', 'systematic', 'intuitive', 'experimental']; return approaches[Math.floor(value) % approaches.length]; case 'depth': return `depth_${Math.floor(value)}`; case 'creativity': return value > 0.7 ? 'high_creativity' : value > 0.3 ? 'medium_creativity' : 'low_creativity'; default: return `${dimension}_${value.toFixed(2)}`; } } /** * Generate completely random action */ generateRandomAction() { const randomActions = [ 'reverse_input', 'combine_unexpected', 'ignore_context', 'amplify_noise', 'invert_logic', 'cross_domain_leap', 'temporal_shift', 'scale_transform' ]; return randomActions[Math.floor(Math.random() * randomActions.length)]; } /** * Execute exploration path */ async executePath(path, input, tools) { let result = input; const executionTrace = []; const MAX_RESULT_SIZE = 5000; // 5KB limit per iteration const MAX_TRACE_ENTRIES = 10; // Limit trace entries for (let i = 0; i < path.length && i < MAX_TRACE_ENTRIES; i++) { const action = path[i]; try { result = await this.executeAction(action, result, tools); // Check and limit result size const resultStr = JSON.stringify(result); if (resultStr.length > MAX_RESULT_SIZE) { result = { truncated: true, action, resultType: typeof result, size: resultStr.length }; } executionTrace.push({ action, result: this.summarizeResult(result) }); } catch (error) { // Handle failures gracefully - they might lead to interesting results executionTrace.push({ action, error: error instanceof Error ? error.message : 'Unknown error' }); // Sometimes continue with modified input if (Math.random() < 0.5) { result = this.generateAlternativeResult(action, result); } } } return { finalResult: result, executionTrace: executionTrace.slice(0, MAX_TRACE_ENTRIES), pathCompleted: executionTrace.length === path.length }; } /** * Execute individual exploration action */ async executeAction(action, input, tools) { if (action.startsWith('select_tool_')) { const toolIndex = parseInt(action.split('_')[2]); // Check if tools exist and index is valid if (!tools || tools.length === 0 || toolIndex < 0) { // Skip tool selection if no tools available or invalid index return input; } const tool = tools[toolIndex % tools.length]; if (!tool) { return input; } return await this.applyTool(tool, input); } if (action.includes('creativity')) { return this.applyCreativeTransform(input, action); } if (action.startsWith('depth_')) { const depth = parseInt(action.split('_')[1]); return this.applyDeepReasoning(input, depth); } // Handle special random actions switch (action) { case 'reverse_input': return this.reverseInput(input); case 'combine_unexpected': return this.combineUnexpected(input, tools); case 'cross_domain_leap': return this.crossDomainLeap(input); default: return this.defaultAction(action, input); } } /** * Calculate novelty compared to exploration history */ calculateNovelty(result, history) { if (history.length === 0) return 1.0; let minSimilarity = 1.0; for (const past of history.slice(-20)) { // Compare with recent history const similarity = this.calculateSimilarity(result, past.output); minSimilarity = Math.min(minSimilarity, similarity); } return 1.0 - minSimilarity; } /** * Calculate surprise level */ calculateSurprise(result, originalInput) { // Measure how different the result is from what would be expected const inputComplexity = this.measureComplexity(originalInput); const outputComplexity = this.measureComplexity(result); const complexityRatio = outputComplexity / Math.max(inputComplexity, 1); // High surprise if output is much more complex or much simpler than input const surpriseFromComplexity = Math.abs(Math.log(complexityRatio)); // Add randomness-based surprise const randomnessSurprise = this.measureRandomness(result); return Math.min(1.0, (surpriseFromComplexity + randomnessSurprise) / 2); } /** * Calculate confidence in result */ calculateConfidence(result) { // Lower confidence for more exploratory results const baseConfidence = 0.5; const temperatureAdjustment = (2.0 - this.currentTemperature) / 2.0; return Math.min(1.0, baseConfidence + temperatureAdjustment * 0.3); } /** * Update exploration temperature (simulated annealing) */ updateTemperature() { this.currentTemperature = Math.max(this.minTemperature, this.currentTemperature * this.coolingRate); } /** * Penalize similar results to encourage diversity */ penalizeSimilarity(newExploration, existing) { for (const exploration of existing) { const similarity = this.calculateSimilarity(newExploration.output, exploration.output); if (similarity > 0.8) { // Reduce novelty score for similar results newExploration.novelty *= (1.0 - similarity * 0.5); } } } // Helper methods for specific transformations async applyTool(tool, input) { // Check if tool is valid if (!tool) { return input; } // For simulation, just return a small mock response instead of actually calling tools // This prevents massive responses from tool arrays return { tool: tool.name || 'unknown', simulated: true, inputSummary: typeof input === 'string' ? input.substring(0, 100) : 'complex_input', mockOutput: `Simulated output from ${tool.name || 'tool'}`, timestamp: Date.now() }; } applyCreativeTransform(input, creativityLevel) { switch (creativityLevel) { case 'high_creativity': return this.highCreativityTransform(input); case 'medium_creativity': return this.mediumCreativityTransform(input); default: return input; } } applyDeepReasoning(input, depth) { // Simulate deep reasoning with depth limit const MAX_DEPTH = 5; // Prevent excessive depth const limitedDepth = Math.min(depth, MAX_DEPTH); let result = input; for (let i = 0; i < limitedDepth; i++) { result = this.reasoningStep(result, i); // Check size and stop if too large if (JSON.stringify(result).length > 2000) { return { reasoning_truncated: true, depth_reached: i, max_depth: limitedDepth }; } } return result; } reverseInput(input) { if (typeof input === 'string') return input.split('').reverse().join(''); if (Array.isArray(input)) return input.slice().reverse(); return input; } combineUnexpected(input, tools) { // Combine random tools in unexpected ways const tool1 = tools[Math.floor(Math.random() * tools.length)]; const tool2 = tools[Math.floor(Math.random() * tools.length)]; return { unexpected_combination: true, tool1_result: tool1.name || 'unknown', tool2_result: tool2.name || 'unknown', original: input }; } crossDomainLeap(input) { const domains = ['mathematics', 'art', 'music', 'biology', 'physics', 'psychology']; const randomDomain = domains[Math.floor(Math.random() * domains.length)]; return { cross_domain_interpretation: true, domain: randomDomain, original: input, transformed: `interpreted_through_${randomDomain}` }; } defaultAction(action, input) { return { action_applied: action, original: input, timestamp: Date.now() }; } // Utility methods calculateSimilarity(a, b) { // Simple similarity calculation const strA = JSON.stringify(a); const strB = JSON.stringify(b); if (strA === strB) return 1.0; const commonLength = Math.max(strA.length, strB.length); let matches = 0; for (let i = 0; i < Math.min(strA.length, strB.length); i++) { if (strA[i] === strB[i]) matches++; } return matches / commonLength; } measureComplexity(obj) { return JSON.stringify(obj).length; } measureRandomness(obj) { // Simple entropy-based randomness measure const str = JSON.stringify(obj); const charCounts = new Map(); for (const char of str) { charCounts.set(char, (charCounts.get(char) || 0) + 1); } let entropy = 0; for (const count of charCounts.values()) { const probability = count / str.length; entropy -= probability * Math.log2(probability); } return entropy / Math.log2(256); // Normalized entropy } summarizeResult(result) { return JSON.stringify(result).substring(0, 100); } generateAlternativeResult(action, input) { return { alternative_generated: true, failed_action: action, alternative_of: input, randomness: Math.random() }; } randomizeParameters(params) { const randomized = { ...params }; for (const [key, value] of Object.entries(randomized)) { if (typeof value === 'number') { // Add some noise to numeric parameters randomized[key] = value * (1 + (Math.random() - 0.5) * 0.2); } } return randomized; } highCreativityTransform(input) { return { creative_transform: 'high', metaphor: this.generateMetaphor(input), abstraction: this.generateAbstraction(input), input_type: typeof input, input_size: JSON.stringify(input).length }; } mediumCreativityTransform(input) { return { creative_transform: 'medium', analogy: this.generateAnalogy(input), input_type: typeof input }; } reasoningStep(input, step) { // Don't nest the entire previous input - just reference it return { reasoning_step: step, previous_type: typeof input, previous_size: JSON.stringify(input).length, inference: `step_${step}_inference`, confidence: Math.random() * 0.5 + 0.5 }; } generateMetaphor(input) { const metaphors = ['ocean wave', 'mountain peak', 'flowing river', 'growing tree', 'burning flame']; return metaphors[Math.floor(Math.random() * metaphors.length)]; } generateAbstraction(input) { const abstractions = ['pattern', 'structure', 'flow', 'emergence', 'transformation']; return abstractions[Math.floor(Math.random() * abstractions.length)]; } generateAnalogy(input) { const analogies = ['like a puzzle piece', 'similar to water flow', 'analogous to growth', 'resembles a dance']; return analogies[Math.floor(Math.random() * analogies.length)]; } /** * Get exploration statistics */ getExplorationStats() { return { totalExplorations: this.explorationHistory.length, currentTemperature: this.currentTemperature, averageNovelty: this.calculateAverageNovelty(), averageSurprise: this.calculateAverageSurprise(), explorationBudget: this.explorationBudget, recentSuccess: this.calculateRecentSuccess() }; } calculateAverageNovelty() { if (this.explorationHistory.length === 0) return 0; const sum = this.explorationHistory.reduce((acc, exp) => acc + exp.novelty, 0); return sum / this.explorationHistory.length; } calculateAverageSurprise() { if (this.explorationHistory.length === 0) return 0; const sum = this.explorationHistory.reduce((acc, exp) => acc + exp.surpriseLevel, 0); return sum / this.explorationHistory.length; } calculateRecentSuccess() { const recent = this.explorationHistory.slice(-10); if (recent.length === 0) return 0; const successful = recent.filter(exp => exp.confidence > 0.6 && exp.novelty > 0.3); return successful.length / recent.length; } }