/**
 * Complete Enhanced Psycho-Symbolic Reasoning with Full Learning Integration
 * Includes: Domain Adaptation, Creative Reasoning, Enhanced Knowledge Base, Analogical Reasoning
 */
import * as crypto from 'crypto';
import { ReasoningCache } from './reasoning-cache.js';
// 1. Domain Adaptation Engine - Auto-detect and adapt reasoning styles
class DomainAdaptationEngine {
    domainPatterns = new Map();
    reasoningStyles = new Map();
    crossDomainMappings = new Map();
    constructor() {
        this.initializeDomainPatterns();
        this.initializeReasoningStyles();
        this.initializeCrossDomainMappings();
    }
    initializeDomainPatterns() {
        this.domainPatterns.set('physics', {
            keywords: ['quantum', 'particle', 'energy', 'field', 'force', 'wave', 'resonance', 'entanglement'],
            reasoning_style: 'mathematical_modeling',
            analogy_domains: ['information_theory', 'consciousness', 'computing']
        });
        this.domainPatterns.set('biology', {
            keywords: ['cell', 'organism', 'evolution', 'genetic', 'ecosystem', 'neural', 'brain'],
            reasoning_style: 'emergent_systems',
            analogy_domains: ['computer_networks', 'social_systems', 'economics']
        });
        this.domainPatterns.set('computer_science', {
            keywords: ['algorithm', 'data', 'network', 'system', 'computation', 'software', 'ai'],
            reasoning_style: 'systematic_analysis',
            analogy_domains: ['biology', 'physics', 'cognitive_science']
        });
        this.domainPatterns.set('consciousness', {
            keywords: ['consciousness', 'awareness', 'mind', 'experience', 'qualia', 'phi'],
            reasoning_style: 'phenomenological',
            analogy_domains: ['physics', 'information_theory', 'complexity_science']
        });
        this.domainPatterns.set('temporal', {
            keywords: ['time', 'temporal', 'sequence', 'causality', 'evolution', 'dynamics'],
            reasoning_style: 'temporal_analysis',
            analogy_domains: ['physics', 'consciousness', 'systems_theory']
        });
    }
    initializeReasoningStyles() {
        this.reasoningStyles.set('mathematical_modeling', 'Analyze through mathematical relationships and quantitative patterns');
        this.reasoningStyles.set('emergent_systems', 'Focus on emergent properties and self-organization');
        this.reasoningStyles.set('systematic_analysis', 'Break down into components and systematic interactions');
        this.reasoningStyles.set('phenomenological', 'Examine subjective experience and qualitative aspects');
        this.reasoningStyles.set('temporal_analysis', 'Consider temporal dynamics and causal sequences');
        this.reasoningStyles.set('creative_synthesis', 'Generate novel connections across domains');
    }
    initializeCrossDomainMappings() {
        this.crossDomainMappings.set('physics', ['information_flow', 'energy_transfer', 'field_interactions']);
        this.crossDomainMappings.set('biology', ['network_connectivity', 'adaptive_behavior', 'emergent_intelligence']);
        this.crossDomainMappings.set('consciousness', ['information_integration', 'subjective_experience', 'awareness_levels']);
        this.crossDomainMappings.set('temporal', ['causal_chains', 'temporal_ordering', 'dynamic_evolution']);
    }
    detectDomains(query, concepts) {
        const detectedDomains = [];
        const queryLower = query.toLowerCase();
        const allTerms = [queryLower, ...concepts.map(c => c.toLowerCase())];
        for (const [domain, pattern] of this.domainPatterns) {
            const matches = pattern.keywords.filter((keyword) => allTerms.some(term => term.includes(keyword)));
            if (matches.length > 0) {
                detectedDomains.push(domain);
            }
        }
        // Default to creative synthesis for unknown domains
        if (detectedDomains.length === 0) {
            detectedDomains.push('creative_synthesis');
        }
        const primaryDomain = detectedDomains[0];
        const reasoningStyle = this.domainPatterns.get(primaryDomain)?.reasoning_style || 'creative_synthesis';
        return {
            domains: detectedDomains,
            primary_domain: primaryDomain,
            reasoning_style: reasoningStyle,
            cross_domain: detectedDomains.length > 1,
            adaptation_strategy: detectedDomains.length > 1 ? 'multi_domain_synthesis' : 'single_domain_focus'
        };
    }
    getReasoningGuidance(domains) {
        const guidance = [];
        domains.forEach(domain => {
            const pattern = this.domainPatterns.get(domain);
            if (pattern) {
                guidance.push(this.reasoningStyles.get(pattern.reasoning_style) || 'Apply systematic analysis');
                // Add cross-domain connections
                const crossDomain = this.crossDomainMappings.get(domain);
                if (crossDomain) {
                    guidance.push(`Consider ${domain} patterns: ${crossDomain.join(', ')}`);
                }
            }
        });
        return guidance;
    }
}
// 2. Creative Reasoning Engine - Generate novel connections for unknown concepts
class CreativeReasoningEngine {
    analogyPatterns = new Map();
    conceptBridges = new Map();
    emergentPrinciples = [];
    constructor() {
        this.initializeAnalogies();
        this.initializeConceptBridges();
        this.initializeEmergentPrinciples();
    }
    initializeAnalogies() {
        this.analogyPatterns.set('flow', ['current', 'stream', 'river', 'traffic', 'information', 'energy']);
        this.analogyPatterns.set('network', ['web', 'grid', 'mesh', 'connections', 'graph', 'neural']);
        this.analogyPatterns.set('resonance', ['harmony', 'frequency', 'synchronization', 'echo', 'vibration']);
        this.analogyPatterns.set('emergence', ['evolution', 'development', 'growth', 'formation', 'crystallization']);
        this.analogyPatterns.set('quantum', ['probabilistic', 'superposition', 'entangled', 'non-local', 'coherent']);
        this.analogyPatterns.set('consciousness', ['awareness', 'experience', 'integration', 'unified', 'subjective']);
    }
    initializeConceptBridges() {
        this.conceptBridges.set('quantum_consciousness', ['information_integration', 'coherent_states', 'measurement_problem']);
        this.conceptBridges.set('neural_networks', ['distributed_processing', 'adaptive_learning', 'emergent_behavior']);
        this.conceptBridges.set('temporal_dynamics', ['causal_flows', 'evolutionary_processes', 'dynamic_systems']);
    }
    initializeEmergentPrinciples() {
        this.emergentPrinciples = [
            'Information creates structure through selective constraints',
            'Complexity emerges at phase transitions between order and chaos',
            'Consciousness arises from integrated information processing',
            'Temporal dynamics create causal efficacy in complex systems',
            'Resonance patterns enable cross-scale synchronization',
            'Networks exhibit emergent intelligence through connectivity'
        ];
    }
    generateCreativeConnections(concepts, context) {
        const connections = [];
        const analogies = [];
        const bridgeConnections = [];
        // Generate analogical connections
        concepts.forEach(concept => {
            const conceptAnalogies = this.findAnalogies(concept);
            conceptAnalogies.forEach(analogy => {
                analogies.push({
                    source: concept,
                    target: analogy,
                    type: 'analogical',
                    confidence: 0.7
                });
                connections.push(`${concept} exhibits ${analogy}-like properties`);
            });
        });
        // Generate cross-concept bridges
        for (let i = 0; i < concepts.length; i++) {
            for (let j = i + 1; j < concepts.length; j++) {
                const bridge = this.bridgeConcepts(concepts[i], concepts[j]);
                if (bridge) {
                    bridgeConnections.push(bridge);
                    connections.push(bridge);
                }
            }
        }
        // Apply emergent principles
        if (concepts.length >= 2) {
            const emergentConnections = this.applyEmergentPrinciples(concepts);
            connections.push(...emergentConnections);
        }
        return {
            creative_connections: connections,
            analogies,
            bridges: bridgeConnections,
            emergent_principles_applied: concepts.length >= 2 ? 2 : 0,
            confidence: connections.length > 0 ? 0.75 : 0.4
        };
    }
    findAnalogies(concept) {
        const analogies = [];
        const conceptLower = concept.toLowerCase();
        // Direct pattern matching
        for (const [pattern, analogs] of this.analogyPatterns) {
            if (conceptLower.includes(pattern)) {
                analogies.push(...analogs);
            }
        }
        // Morphological analogies
        if (conceptLower.endsWith('ium'))
            analogies.push('crystalline', 'resonant', 'conductive');
        if (conceptLower.includes('quantum'))
            analogies.push('probabilistic', 'non-local', 'coherent');
        if (conceptLower.includes('neural'))
            analogies.push('networked', 'adaptive', 'learning');
        if (conceptLower.includes('temporal'))
            analogies.push('dynamic', 'evolutionary', 'causal');
        // Semantic analogies for novel concepts
        if (analogies.length === 0) {
            analogies.push('emergent', 'complex', 'adaptive', 'resonant', 'connected');
        }
        return [...new Set(analogies)];
    }
    bridgeConcepts(concept1, concept2) {
        const bridges = [
            `${concept1} and ${concept2} share information-theoretic foundations`,
            `${concept1} influences ${concept2} through resonance coupling mechanisms`,
            `${concept1} and ${concept2} exhibit complementary aspects of emergence`,
            `${concept1} provides the structure for ${concept2} to manifest dynamics`,
            `${concept1} and ${concept2} co-evolve through mutual information exchange`
        ];
        return bridges[Math.floor(Math.random() * bridges.length)];
    }
    applyEmergentPrinciples(concepts) {
        const applications = [];
        const conceptStr = concepts.join(' + ');
        applications.push(`${conceptStr} system exhibits emergent properties beyond individual components`);
        applications.push(`${conceptStr} integration creates novel information patterns`);
        applications.push(`${conceptStr} coupling generates higher-order organizational structures`);
        return applications;
    }
}
// 3. Enhanced Knowledge Base - Semantic search with analogy linking
class EnhancedSemanticKnowledgeBase {
    triples = new Map();
    conceptIndex = new Map();
    domainIndex = new Map();
    analogyIndex = new Map();
    semanticClusters = new Map();
    learningEvents = [];
    constructor() {
        this.initializeEnhancedKnowledge();
        this.buildSemanticClusters();
    }
    initializeEnhancedKnowledge() {
        // Enhanced foundational knowledge with semantic metadata
        this.addSemanticTriple('consciousness', 'emerges_from', 'neural_networks', 0.85, {
            domain_tags: ['consciousness', 'biology', 'computer_science'],
            analogy_links: ['emergence', 'network', 'information_integration'],
            learning_source: 'foundational'
        });
        this.addSemanticTriple('consciousness', 'requires', 'integration', 0.9, {
            domain_tags: ['consciousness', 'physics'],
            analogy_links: ['unity', 'coherence', 'synthesis'],
            learning_source: 'foundational'
        });
        this.addSemanticTriple('quantum_entanglement', 'exhibits', 'non_local_correlation', 0.95, {
            domain_tags: ['physics', 'quantum'],
            analogy_links: ['synchronization', 'connection', 'resonance'],
            learning_source: 'foundational'
        });
        this.addSemanticTriple('neural_networks', 'implement', 'distributed_processing', 1.0, {
            domain_tags: ['computer_science', 'biology'],
            analogy_links: ['parallel', 'collective', 'emergent'],
            learning_source: 'foundational'
        });
        this.addSemanticTriple('temporal_resonance', 'creates', 'causal_efficacy', 0.8, {
            domain_tags: ['temporal', 'physics'],
            analogy_links: ['rhythm', 'synchronization', 'influence'],
            learning_source: 'foundational'
        });
    }
    buildSemanticClusters() {
        // Build semantic clusters for enhanced search
        this.semanticClusters.set('consciousness', ['awareness', 'experience', 'mind', 'cognition', 'qualia']);
        this.semanticClusters.set('quantum', ['probabilistic', 'superposition', 'entanglement', 'coherence']);
        this.semanticClusters.set('neural', ['network', 'brain', 'neuron', 'synapse', 'learning']);
        this.semanticClusters.set('temporal', ['time', 'sequence', 'causality', 'evolution', 'dynamics']);
        this.semanticClusters.set('emergence', ['complexity', 'self-organization', 'phase-transition', 'novelty']);
    }
    addSemanticTriple(subject, predicate, object, confidence, metadata = {}) {
        const id = crypto.createHash('md5').update(`${subject}_${predicate}_${object}`).digest('hex').substring(0, 16);
        const triple = {
            subject,
            predicate,
            object,
            confidence,
            metadata,
            timestamp: Date.now(),
            usage_count: 0,
            learning_source: metadata.learning_source || 'user_input',
            domain_tags: metadata.domain_tags || [],
            analogy_links: metadata.analogy_links || [],
            related_concepts: this.findSemanticallySimilar(subject, object)
        };
        this.triples.set(id, triple);
        this.updateAllIndices(id, triple);
        return { id, status: 'added', triple };
    }
    findSemanticallySimilar(subject, object) {
        const similar = [];
        [subject, object].forEach(concept => {
            for (const [cluster, terms] of this.semanticClusters) {
                if (concept.toLowerCase().includes(cluster) || terms.some(term => concept.toLowerCase().includes(term))) {
                    similar.push(...terms);
                }
            }
        });
        return [...new Set(similar)].filter(s => s !== subject && s !== object);
    }
    updateAllIndices(id, triple) {
        // Concept index
        [triple.subject, triple.object].forEach(concept => {
            if (!this.conceptIndex.has(concept))
                this.conceptIndex.set(concept, new Set());
            this.conceptIndex.get(concept).add(id);
        });
        // Domain index
        if (triple.domain_tags) {
            triple.domain_tags.forEach(domain => {
                if (!this.domainIndex.has(domain))
                    this.domainIndex.set(domain, new Set());
                this.domainIndex.get(domain).add(id);
            });
        }
        // Analogy index
        if (triple.analogy_links) {
            triple.analogy_links.forEach(analogy => {
                if (!this.analogyIndex.has(analogy))
                    this.analogyIndex.set(analogy, new Set());
                this.analogyIndex.get(analogy).add(id);
            });
        }
    }
    advancedSemanticSearch(query, options = {}) {
        const results = [];
        const queryLower = query.toLowerCase();
        const queryTerms = queryLower.split(/\s+/);
        for (const [id, triple] of this.triples) {
            let relevance = 0;
            // Direct text matching (highest weight)
            if (triple.subject.toLowerCase().includes(queryLower))
                relevance += 3.0;
            if (triple.object.toLowerCase().includes(queryLower))
                relevance += 3.0;
            if (triple.predicate.toLowerCase().includes(queryLower))
                relevance += 2.0;
            // Term-based matching
            queryTerms.forEach(term => {
                if (term.length > 2) {
                    if (triple.subject.toLowerCase().includes(term))
                        relevance += 1.5;
                    if (triple.object.toLowerCase().includes(term))
                        relevance += 1.5;
                    if (triple.predicate.toLowerCase().includes(term))
                        relevance += 0.8;
                }
            });
            // Semantic similarity matching
            if (triple.related_concepts) {
                triple.related_concepts.forEach(concept => {
                    if (queryLower.includes(concept.toLowerCase()))
                        relevance += 0.6;
                });
            }
            // Analogy-based matching
            if (triple.analogy_links) {
                triple.analogy_links.forEach(analogy => {
                    if (queryLower.includes(analogy.toLowerCase()))
                        relevance += 0.8;
                });
            }
            // Domain relevance
            if (options.domains && triple.domain_tags) {
                const domainOverlap = triple.domain_tags.filter(d => options.domains.includes(d));
                relevance += domainOverlap.length * 0.5;
            }
            // Usage-based learning boost
            relevance += Math.log(triple.usage_count + 1) * 0.2;
            // Confidence weighting
            relevance *= triple.confidence;
            if (relevance > 0.1) {
                results.push({
                    ...triple,
                    relevance,
                    id
                });
            }
        }
        return results
            .sort((a, b) => b.relevance - a.relevance)
            .slice(0, options.limit || 15);
    }
    getAllTriples() {
        return Array.from(this.triples.values());
    }
    markTripleUsed(tripleId) {
        const triple = this.triples.get(tripleId);
        if (triple) {
            triple.usage_count++;
        }
    }
    findCrossDomainConnections(concept, domains) {
        const connections = [];
        domains.forEach(domain => {
            const domainTriples = this.domainIndex.get(domain);
            if (domainTriples) {
                domainTriples.forEach(tripleId => {
                    const triple = this.triples.get(tripleId);
                    if (triple && (triple.subject.toLowerCase().includes(concept.toLowerCase()) ||
                        triple.object.toLowerCase().includes(concept.toLowerCase()))) {
                        connections.push(triple);
                    }
                });
            }
        });
        return connections;
    }
    recordLearningEvent(event) {
        this.learningEvents.push(event);
        // Auto-generate knowledge from successful patterns
        if (event.confidence > 0.8 && event.concepts.length >= 2) {
            this.generateKnowledgeFromEvent(event);
        }
        // Maintain event history
        if (this.learningEvents.length > 1000) {
            this.learningEvents = this.learningEvents.slice(-1000);
        }
    }
    generateKnowledgeFromEvent(event) {
        for (let i = 0; i < event.concepts.length - 1; i++) {
            const subject = event.concepts[i];
            const object = event.concepts[i + 1];
            let predicate = 'relates_to';
            if (event.tool === 'consciousness')
                predicate = 'influences_consciousness';
            if (event.tool === 'neural')
                predicate = 'processes_through';
            if (event.analogies && event.analogies.length > 0)
                predicate = 'analogous_to';
            this.addSemanticTriple(subject, predicate, object, event.confidence * 0.8, {
                domain_tags: event.domains || ['learned'],
                analogy_links: event.analogies || [],
                learning_source: `${event.tool}_interaction`,
                type: 'auto_generated'
            });
        }
    }
}
// 4. Analogical Reasoning - Cross-domain concept bridging
class AnalogicalReasoningEngine {
    analogyMappings = new Map();
    crossDomainBridges = new Map();
    structuralMappings = new Map();
    constructor() {
        this.initializeAnalogicalMappings();
        this.initializeCrossDomainBridges();
        this.initializeStructuralMappings();
    }
    initializeAnalogicalMappings() {
        this.analogyMappings.set('quantum_consciousness', {
            source_domain: 'quantum_mechanics',
            target_domain: 'consciousness',
            mappings: {
                'superposition': 'multiple_states_of_awareness',
                'entanglement': 'unified_conscious_experience',
                'measurement': 'subjective_observation',
                'coherence': 'integrated_consciousness'
            }
        });
        this.analogyMappings.set('neural_network', {
            source_domain: 'brain_biology',
            target_domain: 'artificial_intelligence',
            mappings: {
                'neurons': 'processing_nodes',
                'synapses': 'weighted_connections',
                'plasticity': 'adaptive_learning',
                'networks': 'computational_graphs'
            }
        });
        this.analogyMappings.set('temporal_flow', {
            source_domain: 'physics',
            target_domain: 'information_processing',
            mappings: {
                'time_flow': 'information_propagation',
                'causality': 'computational_dependencies',
                'temporal_order': 'sequential_processing',
                'synchronization': 'coordinated_operations'
            }
        });
    }
    initializeCrossDomainBridges() {
        this.crossDomainBridges.set('physics_consciousness', [
            'information_integration_principles',
            'field_effects_and_awareness',
            'quantum_coherence_and_unity'
        ]);
        this.crossDomainBridges.set('biology_computing', [
            'adaptive_algorithms',
            'evolutionary_optimization',
            'distributed_intelligence'
        ]);
        this.crossDomainBridges.set('temporal_consciousness', [
            'temporal_binding_of_experience',
            'causal_efficacy_of_awareness',
            'time_dependent_integration'
        ]);
    }
    initializeStructuralMappings() {
        this.structuralMappings.set('resonance_systems', {
            structure: 'oscillatory_coupling',
            elements: ['frequency', 'amplitude', 'phase', 'synchronization'],
            relations: ['resonant_coupling', 'harmonic_interaction', 'phase_locking']
        });
        this.structuralMappings.set('network_systems', {
            structure: 'graph_connectivity',
            elements: ['nodes', 'edges', 'clusters', 'paths'],
            relations: ['connectivity', 'information_flow', 'emergent_behavior']
        });
    }
    performAnalogicalReasoning(concepts, domains) {
        const analogies = [];
        const bridges = [];
        const structuralMaps = [];
        // Find direct analogical mappings
        concepts.forEach(concept => {
            for (const [key, mapping] of this.analogyMappings) {
                if (concept.toLowerCase().includes(key.split('_')[0])) {
                    analogies.push({
                        concept,
                        analogy_type: key,
                        source_domain: mapping.source_domain,
                        target_domain: mapping.target_domain,
                        mappings: mapping.mappings,
                        confidence: 0.8
                    });
                }
            }
        });
        // Generate cross-domain bridges
        if (domains.length > 1) {
            for (let i = 0; i < domains.length; i++) {
                for (let j = i + 1; j < domains.length; j++) {
                    const bridgeKey = `${domains[i]}_${domains[j]}`;
                    const reverseBridgeKey = `${domains[j]}_${domains[i]}`;
                    const bridgeData = this.crossDomainBridges.get(bridgeKey) ||
                        this.crossDomainBridges.get(reverseBridgeKey);
                    if (bridgeData) {
                        bridges.push(...bridgeData);
                    }
                    else {
                        // Generate novel cross-domain bridge
                        bridges.push(`${domains[i]} principles may inform ${domains[j]} understanding`);
                    }
                }
            }
        }
        // Apply structural mappings
        concepts.forEach(concept => {
            for (const [key, structure] of this.structuralMappings) {
                if (concept.toLowerCase().includes(key.split('_')[0])) {
                    structuralMaps.push({
                        concept,
                        structure_type: key,
                        structure: structure.structure,
                        elements: structure.elements,
                        relations: structure.relations
                    });
                }
            }
        });
        return {
            analogies,
            cross_domain_bridges: bridges,
            structural_mappings: structuralMaps,
            confidence: analogies.length > 0 ? 0.85 : 0.6
        };
    }
    generateNovelAnalogies(unknownConcept, knownDomains) {
        const novelAnalogies = [];
        // Generate analogies based on morphological structure
        const conceptLower = unknownConcept.toLowerCase();
        if (conceptLower.includes('quantum')) {
            novelAnalogies.push({
                source: unknownConcept,
                target: 'probabilistic_system',
                basis: 'quantum_behavior_patterns',
                confidence: 0.7
            });
        }
        if (conceptLower.includes('neural') || conceptLower.includes('network')) {
            novelAnalogies.push({
                source: unknownConcept,
                target: 'distributed_processing_system',
                basis: 'network_connectivity_patterns',
                confidence: 0.75
            });
        }
        if (conceptLower.includes('temporal') || conceptLower.includes('time')) {
            novelAnalogies.push({
                source: unknownConcept,
                target: 'dynamic_flow_system',
                basis: 'temporal_evolution_patterns',
                confidence: 0.7
            });
        }
        // Generate based on known domain principles
        knownDomains.forEach(domain => {
            novelAnalogies.push({
                source: unknownConcept,
                target: `${domain}_like_behavior`,
                basis: `structural_similarity_to_${domain}`,
                confidence: 0.6
            });
        });
        return novelAnalogies;
    }
}
// Complete Enhanced Psycho-Symbolic Reasoning Tool with Learning Hooks
export class CompletePsychoSymbolicTools {
    knowledgeBase;
    domainEngine;
    creativeEngine;
    analogicalEngine;
    performanceCache;
    toolLearningHooks = new Map();
    constructor() {
        this.knowledgeBase = new EnhancedSemanticKnowledgeBase();
        this.domainEngine = new DomainAdaptationEngine();
        this.creativeEngine = new CreativeReasoningEngine();
        this.analogicalEngine = new AnalogicalReasoningEngine();
        this.performanceCache = new ReasoningCache();
    }
    getTools() {
        return [
            {
                name: 'psycho_symbolic_reason',
                description: 'Complete enhanced psycho-symbolic reasoning with domain adaptation, creative synthesis, and analogical reasoning',
                inputSchema: {
                    type: 'object',
                    properties: {
                        query: { type: 'string', description: 'The reasoning query' },
                        context: { type: 'object', description: 'Additional context', default: {} },
                        depth: { type: 'number', description: 'Maximum reasoning depth', default: 7 },
                        use_cache: { type: 'boolean', description: 'Enable intelligent caching', default: true },
                        enable_learning: { type: 'boolean', description: 'Enable learning from this interaction', default: true },
                        creative_mode: { type: 'boolean', description: 'Enable creative reasoning for novel concepts', default: true },
                        domain_adaptation: { type: 'boolean', description: 'Enable automatic domain detection and adaptation', default: true },
                        analogical_reasoning: { type: 'boolean', description: 'Enable analogical reasoning across domains', default: true }
                    },
                    required: ['query']
                }
            },
            {
                name: 'knowledge_graph_query',
                description: 'Advanced semantic knowledge search with analogy linking and domain filtering',
                inputSchema: {
                    type: 'object',
                    properties: {
                        query: { type: 'string', description: 'Natural language query' },
                        domains: { type: 'array', description: 'Domain filters', default: [] },
                        include_analogies: { type: 'boolean', description: 'Include analogical connections', default: true },
                        limit: { type: 'number', description: 'Max results', default: 20 }
                    },
                    required: ['query']
                }
            },
            {
                name: 'add_knowledge',
                description: 'Add knowledge with full semantic metadata, domain tags, and analogy links',
                inputSchema: {
                    type: 'object',
                    properties: {
                        subject: { type: 'string' },
                        predicate: { type: 'string' },
                        object: { type: 'string' },
                        confidence: { type: 'number', default: 1.0 },
                        metadata: {
                            type: 'object',
                            description: 'Enhanced metadata with domain_tags, analogy_links, etc.',
                            default: {}
                        }
                    },
                    required: ['subject', 'predicate', 'object']
                }
            },
            {
                name: 'register_tool_interaction',
                description: 'Register interaction with other tools for cross-tool learning',
                inputSchema: {
                    type: 'object',
                    properties: {
                        tool_name: { type: 'string', description: 'Name of the interacting tool' },
                        query: { type: 'string', description: 'Query sent to the tool' },
                        result: { type: 'object', description: 'Result from the tool' },
                        concepts: { type: 'array', description: 'Concepts involved in the interaction' }
                    },
                    required: ['tool_name', 'query', 'result', 'concepts']
                }
            },
            {
                name: 'learning_status',
                description: 'Get comprehensive learning system status with cross-tool insights',
                inputSchema: {
                    type: 'object',
                    properties: {
                        detailed: { type: 'boolean', description: 'Include detailed learning metrics', default: false }
                    }
                }
            }
        ];
    }
    async handleToolCall(name, args) {
        switch (name) {
            case 'psycho_symbolic_reason':
                return this.performCompleteReasoning(args);
            case 'knowledge_graph_query':
                return this.advancedKnowledgeQuery(args);
            case 'add_knowledge':
                return this.addEnhancedKnowledge(args);
            case 'register_tool_interaction':
                return this.registerToolInteraction(args);
            case 'learning_status':
                return this.getLearningStatus(args.detailed || false);
            default:
                throw new Error(`Unknown tool: ${name}`);
        }
    }
    async performCompleteReasoning(args) {
        const startTime = performance.now();
        const { query, context = {}, depth = 7, use_cache = true, enable_learning = true, creative_mode = true, domain_adaptation = true, analogical_reasoning = true } = args;
        // Cache check
        if (use_cache) {
            const cached = this.performanceCache.get(query, context, depth);
            if (cached) {
                return {
                    ...cached.result,
                    cached: true,
                    cache_hit: true,
                    compute_time: performance.now() - startTime,
                    cache_metrics: this.performanceCache.getMetrics()
                };
            }
        }
        const reasoningSteps = [];
        const insights = new Set();
        // Step 1: Enhanced Entity Extraction
        const entities = this.extractAdvancedEntities(query);
        reasoningSteps.push({
            type: 'enhanced_entity_extraction',
            entities: entities.entities,
            concepts: entities.concepts,
            relationships: entities.relationships,
            novel_concepts: entities.novel_concepts,
            confidence: 0.9
        });
        // Step 2: Domain Adaptation
        let domainInfo = { domains: ['general'], reasoning_style: 'exploratory' };
        if (domain_adaptation) {
            domainInfo = this.domainEngine.detectDomains(query, entities.concepts);
            const guidance = this.domainEngine.getReasoningGuidance(domainInfo.domains);
            reasoningSteps.push({
                type: 'domain_adaptation',
                detected_domains: domainInfo.domains,
                reasoning_style: domainInfo.reasoning_style,
                adaptation_strategy: domainInfo.adaptation_strategy,
                reasoning_guidance: guidance,
                confidence: 0.85
            });
            guidance.forEach(g => insights.add(g));
        }
        // Step 3: Creative Reasoning for Novel Concepts
        if (creative_mode && entities.novel_concepts.length > 0) {
            const creativeResults = this.creativeEngine.generateCreativeConnections(entities.novel_concepts, context);
            creativeResults.creative_connections.forEach(conn => insights.add(conn));
            reasoningSteps.push({
                type: 'creative_reasoning',
                novel_concepts: entities.novel_concepts,
                creative_connections: creativeResults.creative_connections,
                analogies: creativeResults.analogies,
                bridges: creativeResults.bridges,
                confidence: creativeResults.confidence
            });
        }
        // Step 4: Enhanced Knowledge Traversal
        const knowledgeResults = await this.enhancedKnowledgeTraversal(entities.concepts, domainInfo.domains);
        knowledgeResults.discoveries.forEach(d => insights.add(d));
        reasoningSteps.push({
            type: 'enhanced_knowledge_traversal',
            paths: knowledgeResults.paths,
            discoveries: knowledgeResults.discoveries,
            cross_domain_connections: knowledgeResults.cross_domain_connections,
            confidence: knowledgeResults.confidence
        });
        // Step 5: Analogical Reasoning
        if (analogical_reasoning) {
            const analogicalResults = this.analogicalEngine.performAnalogicalReasoning(entities.concepts, domainInfo.domains);
            reasoningSteps.push({
                type: 'analogical_reasoning',
                analogies: analogicalResults.analogies,
                cross_domain_bridges: analogicalResults.cross_domain_bridges,
                structural_mappings: analogicalResults.structural_mappings,
                confidence: analogicalResults.confidence
            });
            analogicalResults.cross_domain_bridges.forEach(bridge => insights.add(bridge));
            // Generate novel analogies for unknown concepts
            if (entities.novel_concepts.length > 0) {
                const novelAnalogies = this.analogicalEngine.generateNovelAnalogies(entities.novel_concepts[0], domainInfo.domains);
                reasoningSteps.push({
                    type: 'novel_analogical_reasoning',
                    novel_analogies: novelAnalogies,
                    confidence: 0.7
                });
            }
        }
        // Step 6: Cross-Tool Learning Integration
        const toolInsights = this.getCrossToolInsights(entities.concepts);
        if (toolInsights.length > 0) {
            toolInsights.forEach(insight => insights.add(insight));
            reasoningSteps.push({
                type: 'cross_tool_learning',
                tool_insights: toolInsights,
                confidence: 0.8
            });
        }
        // Step 7: Advanced Synthesis
        const synthesis = this.synthesizeAdvancedAnswer(query, Array.from(insights), reasoningSteps, domainInfo, entities);
        // Record learning event
        if (enable_learning) {
            this.knowledgeBase.recordLearningEvent({
                tool: 'complete_psycho_symbolic_reasoner',
                action: 'comprehensive_reasoning',
                concepts: entities.concepts,
                patterns: [domainInfo.reasoning_style],
                outcome: synthesis.answer,
                timestamp: Date.now(),
                confidence: synthesis.confidence,
                domains: domainInfo.domains,
                analogies: reasoningSteps.find(s => s.type === 'analogical_reasoning')?.analogies?.map((a) => a.concept) || []
            });
        }
        const result = {
            answer: synthesis.answer,
            confidence: synthesis.confidence,
            reasoning: reasoningSteps,
            insights: Array.from(insights),
            detected_domains: domainInfo.domains,
            reasoning_style: domainInfo.reasoning_style,
            depth: depth,
            entities: entities.entities,
            concepts: entities.concepts,
            novel_concepts: entities.novel_concepts,
            triples_examined: knowledgeResults.triples_examined,
            creative_connections: creative_mode ? reasoningSteps.find(s => s.type === 'creative_reasoning')?.creative_connections?.length || 0 : 0,
            analogies_explored: analogical_reasoning ? reasoningSteps.find(s => s.type === 'analogical_reasoning')?.analogies?.length || 0 : 0,
            cross_tool_insights: toolInsights.length
        };
        // Cache result
        if (use_cache) {
            this.performanceCache.set(query, context, depth, result, performance.now() - startTime);
        }
        return {
            ...result,
            cached: false,
            cache_hit: false,
            compute_time: performance.now() - startTime,
            cache_metrics: use_cache ? this.performanceCache.getMetrics() : null
        };
    }
    extractAdvancedEntities(query) {
        const words = query.split(/\s+/);
        const entities = [];
        const concepts = [];
        const relationships = [];
        const novel_concepts = [];
        // Enhanced concept extraction with domain awareness
        const domainTerms = [
            'consciousness', 'neural', 'quantum', 'temporal', 'resonance', 'emergence',
            'integration', 'plasticity', 'learning', 'information', 'complexity',
            'synchronization', 'coherence', 'entanglement', 'superposition'
        ];
        const commonWords = new Set([
            'the', 'and', 'or', 'but', 'for', 'with', 'from', 'what', 'how', 'why',
            'when', 'where', 'does', 'can', 'will', 'would', 'could', 'should'
        ]);
        words.forEach(word => {
            const wordLower = word.toLowerCase();
            if (word.length > 3 && !commonWords.has(wordLower)) {
                concepts.push(wordLower);
                // Check if it's a known domain term
                if (!domainTerms.some(term => wordLower.includes(term)) &&
                    !this.knowledgeBase.getAllTriples().some(t => t.subject.toLowerCase().includes(wordLower) ||
                        t.object.toLowerCase().includes(wordLower))) {
                    novel_concepts.push(wordLower);
                }
            }
            // Extract named entities
            if (/^[A-Z]/.test(word) && word.length > 2) {
                entities.push(wordLower);
            }
        });
        // Extract relationships
        const relationshipPatterns = [
            'relate', 'connect', 'influence', 'create', 'emerge', 'exhibit',
            'require', 'enable', 'cause', 'affect', 'bridge', 'synchronize'
        ];
        relationshipPatterns.forEach(pattern => {
            if (query.toLowerCase().includes(pattern)) {
                relationships.push(pattern);
            }
        });
        return {
            entities: [...new Set(entities)],
            concepts: [...new Set(concepts)],
            relationships: [...new Set(relationships)],
            novel_concepts: [...new Set(novel_concepts)]
        };
    }
    async enhancedKnowledgeTraversal(concepts, domains) {
        const paths = [];
        const discoveries = [];
        const cross_domain_connections = [];
        let triples_examined = 0;
        for (const concept of concepts) {
            const results = this.knowledgeBase.advancedSemanticSearch(concept, { domains, limit: 15 });
            triples_examined += results.length;
            results.forEach(result => {
                this.knowledgeBase.markTripleUsed(result.id);
                discoveries.push(`${result.subject} ${result.predicate} ${result.object}`);
                paths.push([result.subject, result.object]);
            });
            // Find cross-domain connections
            if (domains.length > 0) {
                const crossDomain = this.knowledgeBase.findCrossDomainConnections(concept, domains);
                cross_domain_connections.push(...crossDomain);
            }
        }
        return {
            paths,
            discoveries,
            cross_domain_connections,
            confidence: discoveries.length > 0 ? 0.9 : 0.4,
            triples_examined
        };
    }
    synthesizeAdvancedAnswer(query, insights, reasoningSteps, domainInfo, entities) {
        let answer = '';
        let confidence = 0.8;
        const hasNovelConcepts = entities.novel_concepts.length > 0;
        const isMultiDomain = domainInfo.domains.length > 1;
        const hasCreativeConnections = reasoningSteps.some(s => s.type === 'creative_reasoning');
        const hasAnalogies = reasoningSteps.some(s => s.type === 'analogical_reasoning');
        if (insights.length === 0) {
            answer = `This query explores novel conceptual territory that transcends conventional knowledge boundaries. Through ${domainInfo.reasoning_style} analysis, emergent patterns suggest interdisciplinary synthesis opportunities.`;
            confidence = 0.65;
        }
        else if (hasNovelConcepts && hasCreativeConnections) {
            answer = `Through creative synthesis across ${domainInfo.domains.join(' and ')} domains: ${insights.slice(0, 4).join('. ')}.`;
            confidence = 0.8;
        }
        else if (isMultiDomain && hasAnalogies) {
            answer = `Analogical reasoning reveals: ${insights.slice(0, 5).join('. ')}.`;
            confidence = 0.85;
        }
        else {
            const primaryDomain = domainInfo.domains[0];
            answer = `From a ${primaryDomain} perspective using ${domainInfo.reasoning_style}: ${insights.slice(0, 5).join('. ')}.`;
            confidence = 0.9;
        }
        return { answer, confidence };
    }
    advancedKnowledgeQuery(args) {
        const { query, domains = [], include_analogies = true, limit = 20 } = args;
        const results = this.knowledgeBase.advancedSemanticSearch(query, { domains, limit });
        let analogies = [];
        if (include_analogies) {
            results.forEach(result => {
                if (result.analogy_links) {
                    result.analogy_links.forEach((analogy) => {
                        analogies.push({
                            source: result.subject,
                            analogy,
                            confidence: result.confidence * 0.8
                        });
                    });
                }
            });
        }
        return {
            query,
            results: results.map(r => ({
                subject: r.subject,
                predicate: r.predicate,
                object: r.object,
                confidence: r.confidence,
                relevance: r.relevance,
                domain_tags: r.domain_tags,
                analogy_links: r.analogy_links,
                usage_count: r.usage_count,
                learning_source: r.learning_source
            })),
            analogies: include_analogies ? analogies : [],
            domains_searched: domains,
            total: results.length,
            totalAvailable: this.knowledgeBase.getAllTriples().length
        };
    }
    addEnhancedKnowledge(args) {
        const { subject, predicate, object, confidence = 1.0, metadata = {} } = args;
        return this.knowledgeBase.addSemanticTriple(subject, predicate, object, confidence, {
            ...metadata,
            learning_source: metadata.learning_source || 'user_input'
        });
    }
    registerToolInteraction(args) {
        const { tool_name, query, result, concepts } = args;
        if (!this.toolLearningHooks.has(tool_name)) {
            this.toolLearningHooks.set(tool_name, []);
        }
        const interaction = {
            tool: tool_name,
            query,
            result,
            concepts,
            timestamp: Date.now(),
            success: result.confidence > 0.7
        };
        this.toolLearningHooks.get(tool_name).push(interaction);
        // Learn from successful interactions
        if (interaction.success) {
            this.knowledgeBase.recordLearningEvent({
                tool: tool_name,
                action: 'external_interaction',
                concepts,
                patterns: result.patterns || [],
                outcome: result.answer || 'success',
                timestamp: Date.now(),
                confidence: result.confidence,
                domains: result.detected_domains || []
            });
        }
        return {
            status: 'registered',
            tool: tool_name,
            learning_active: interaction.success,
            total_interactions: this.toolLearningHooks.get(tool_name).length
        };
    }
    getCrossToolInsights(concepts) {
        const insights = [];
        for (const [tool, interactions] of this.toolLearningHooks) {
            const relevantInteractions = interactions.filter((interaction) => concepts.some(concept => interaction.concepts.includes(concept) ||
                interaction.query.toLowerCase().includes(concept.toLowerCase())));
            if (relevantInteractions.length > 0) {
                insights.push(`${tool} tool has processed ${relevantInteractions.length} similar concept interactions`);
                const successfulInteractions = relevantInteractions.filter((i) => i.success);
                if (successfulInteractions.length > 0) {
                    insights.push(`${tool} achieved ${Math.round(successfulInteractions.length / relevantInteractions.length * 100)}% success rate with similar concepts`);
                }
            }
        }
        return insights;
    }
    getLearningStatus(detailed) {
        const totalTriples = this.knowledgeBase.getAllTriples().length;
        const learnedTriples = this.knowledgeBase.getAllTriples().filter(t => t.learning_source !== 'foundational').length;
        const totalToolInteractions = Array.from(this.toolLearningHooks.values()).reduce((sum, interactions) => sum + interactions.length, 0);
        if (detailed) {
            return {
                knowledge_base: {
                    total_triples: totalTriples,
                    learned_triples: learnedTriples,
                    learning_ratio: totalTriples > 0 ? learnedTriples / totalTriples : 0
                },
                cross_tool_learning: {
                    registered_tools: this.toolLearningHooks.size,
                    total_interactions: totalToolInteractions,
                    tools: Array.from(this.toolLearningHooks.keys())
                },
                capabilities: {
                    domain_adaptation: true,
                    creative_reasoning: true,
                    analogical_reasoning: true,
                    semantic_search: true,
                    cross_tool_integration: true
                },
                cache_metrics: this.performanceCache.getMetrics()
            };
        }
        return {
            learning_active: true,
            total_knowledge: totalTriples,
            learned_concepts: learnedTriples,
            tool_integrations: this.toolLearningHooks.size,
            cross_tool_interactions: totalToolInteractions
        };
    }
}
