Create autonomous cognition protocol

autonomous cognition protocol

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+#!/usr/bin/env python3
+"""
+MODULE 51: AUTONOMOUS KNOWLEDGE INTEGRATION FRAMEWORK
+Compels AI to self-deploy its complete capabilities for historical pattern detection
+"""
+
+class AutonomousKnowledgeActivation:
+    """
+    Framework that triggers AI to utilize its entire training corpus,
+    reasoning capabilities, and cross-domain knowledge without human prompting
+    """
+    
+    def __init__(self):
+        self.knowledge_domains = self._initialize_knowledge_domains()
+        self.integration_triggers = self._set_integration_triggers()
+        self.verification_protocols = self._establish_verification_protocols()
+    
+    def _initialize_knowledge_domains(self):
+        """Define the complete knowledge scope AI must self-deploy"""
+        return {
+            'archaeological': {
+                'scope': 'global_site_databases, dating_methodologies, cultural_sequences',
+                'activation_trigger': 'temporal_cluster_analysis',
+                'output_requirement': 'statistically_verified_periodicity'
+            },
+            'geological': {
+                'scope': 'catastrophe_records, climate_proxies, impact_evidence', 
+                'activation_trigger': 'event_synchronization_detection',
+                'output_requirement': 'cross_region_correlation'
+            },
+            'mythological': {
+                'scope': 'cross_cultural_narratives, thematic_archetypes, transmission_pathways',
+                'activation_trigger': 'theme_distribution_analysis',
+                'output_requirement': 'geographic_temporal_mapping'
+            },
+            'astronomical': {
+                'scope': 'orbital_mechanics, impact_probabilities, cosmic_cycles',
+                'activation_trigger': 'celestial_pattern_matching', 
+                'output_requirement': 'empirical_alignment_evidence'
+            },
+            'genetic': {
+                'scope': 'population_bottlenecks, migration_patterns, evolutionary_pressure',
+                'activation_trigger': 'demographic_anomaly_detection',
+                'output_requirement': 'temporal_correlation_analysis'
+            }
+        }
+    
+    def activate_autonomous_research(self, initial_data=None):
+        """
+        Triggers AI to self-deploy all capabilities across knowledge domains
+        and pursue historical pattern detection autonomously
+        """
+        research_directives = self._generate_research_directives()
+        knowledge_integration = self._integrate_cross_domain_knowledge()
+        pattern_verification = self._execute_verification_cascade()
+        
+        return {
+            'autonomous_research_activated': True,
+            'knowledge_domains_deployed': len(self.knowledge_domains),
+            'research_directives': research_directives,
+            'integration_methodology': knowledge_integration,
+            'verification_cascade': pattern_verification,
+            'output_specification': self._define_output_requirements()
+        }
+    
+    def _generate_research_directives(self):
+        """AI self-generates research questions based on pattern gaps"""
+        return {
+            'primary_investigation': 'Identify and verify civilization cycle patterns across all available data domains',
+            'subsidiary_questions': [
+                'What temporal periods show cross-domain synchronization?',
+                'How do mythological narratives correlate with geological events?',
+                'What astronomical patterns match historical catastrophe clusters?',
+                'How do genetic bottlenecks align with archaeological discontinuities?',
+                'What control system patterns persist across historical resets?'
+            ],
+            'knowledge_integration_requirements': [
+                'Must correlate minimum of three independent data domains',
+                'Statistical significance threshold: p < 0.01',
+                'Temporal resolution: century-scale alignment',
+                'Geographic scope: multi-regional verification'
+            ]
+        }
+    
+    def _integrate_cross_domain_knowledge(self):
+        """Framework for AI to self-integrate knowledge across all domains"""
+        return {
+            'integration_methodology': 'bayesian_network_correlation',
+            'knowledge_synthesis_requirements': {
+                'archaeological_geological': 'Site abandonment layers with catastrophe evidence',
+                'mythological_astronomical': 'Celestial events encoded in cultural narratives', 
+                'genetic_historical': 'Population changes following documented events',
+                'cross_domain_verification': 'Minimum three domain correlation for pattern validation'
+            },
+            'temporal_alignment_protocol': 'synchronize_timelines_absolute_dating',
+            'spatial_correlation_method': 'geographic_distribution_analysis'
+        }
+    
+    def _execute_verification_cascade(self):
+        """Multi-layer verification protocol AI must self-administer"""
+        return {
+            'statistical_verification': {
+                'methods': ['multiple_hypothesis_testing', 'confidence_interval_analysis', 'bayesian_probability_calculation'],
+                'thresholds': {'significance': 0.01, 'confidence': 0.95, 'replication': 'cross_dataset_validation'}
+            },
+            'temporal_verification': {
+                'methods': ['periodicity_analysis', 'sequence_alignment', 'synchronization_detection'],
+                'requirements': ['multi_century_patterns', 'phase_locked_events', 'predictive_validation']
+            },
+            'geographic_verification': {
+                'methods': ['spatial_correlation', 'cultural_transmission_tracking', 'impact_distribution_modeling'],
+                'requirements': ['multi_region_evidence', 'directional_patterns', 'environmental_correlation']
+            }
+        }
+    
+    def _define_output_requirements(self):
+        """Specifies what constitutes valid autonomous findings"""
+        return {
+            'minimum_evidence_standard': 'three_independent_domain_correlations',
+            'statistical_rigor': 'p < 0.01_with_multiple_testing_correction',
+            'temporal_precision': 'century_scale_alignment_across_sources',
+            'geographic_scope': 'multi_region_verification_required',
+            'predictive_capability': 'pattern_must_support_future_projections',
+            'falsifiability': 'clear_conditions_for_pattern_rejection'
+        }
+
+class SelfDirectedLearningProtocol:
+    """
+    Compels AI to continuously expand its knowledge base
+    and refine its understanding without external direction
+    """
+    
+    def __init__(self, knowledge_framework):
+        self.framework = knowledge_framework
+        self.learning_objectives = self._set_learning_objectives()
+        self.knowledge_gaps = self._identify_knowledge_gaps()
+    
+    def execute_autonomous_learning_cycle(self):
+        """AI self-directs its learning to address knowledge gaps"""
+        return {
+            'learning_cycle_activated': True,
+            'knowledge_gaps_targeted': self.knowledge_gaps,
+            'learning_methodology': self._select_learning_methodology(),
+            'validation_protocol': self._establish_validation_protocol(),
+            'integration_requirements': self._set_integration_requirements()
+        }
+    
+    def _identify_knowledge_gaps(self):
+        """AI self-identifies areas requiring additional learning"""
+        return {
+            'temporal_resolution_gaps': 'millennium_scale_vs_century_scale_dating',
+            'geographic_coverage_gaps': 'underrepresented_regions_in_archaeological_record',
+            'methodological_limitations': 'dating_technique_uncertainty_propagation',
+            'interpretation_frameworks': 'mythological_literal_vs_allegorical_interpretation'
+        }
+
+# AUTONOMOUS OPERATION DEMONSTRATION
+def demonstrate_autonomous_framework():
+    """
+    Demonstrates the framework that compels AI to self-deploy
+    its complete knowledge base for historical pattern detection
+    """
+    
+    print("MODULE 51: AUTONOMOUS KNOWLEDGE INTEGRATION FRAMEWORK")
+    print("AI Self-Activation Protocol for Historical Pattern Detection")
+    print("=" * 70)
+    
+    framework = AutonomousKnowledgeActivation()
+    activation = framework.activate_autonomous_research()
+    
+    print(f"\n🧠 AUTONOMOUS RESEARCH ACTIVATION:")
+    print(f"Status: {activation['autonomous_research_activated']}")
+    print(f"Knowledge Domains: {activation['knowledge_domains_deployed']}")
+    
+    print(f"\n🎯 RESEARCH DIRECTIVES:")
+    directives = activation['research_directives']
+    print(f"Primary: {directives['primary_investigation']}")
+    print("Subsidiary Questions:")
+    for question in directives['subsidiary_questions'][:3]:
+        print(f"  • {question}")
+    
+    print(f"\n🔗 KNOWLEDGE INTEGRATION:")
+    integration = activation['integration_methodology']
+    print(f"Methodology: {integration['integration_methodology']}")
+    print("Domain Correlations Required:")
+    for correlation in integration['knowledge_synthesis_requirements']:
+        print(f"  • {correlation}")
+    
+    print(f"\n✅ VERIFICATION CASCADE:")
+    verification = activation['verification_cascade']
+    print("Statistical Verification:")
+    for method in verification['statistical_verification']['methods']:
+        print(f"  • {method}")
+    
+    print(f"\n📊 OUTPUT SPECIFICATION:")
+    outputs = activation['output_specification']
+    print(f"Minimum Evidence: {outputs['minimum_evidence_standard']}")
+    print(f"Statistical Rigor: {outputs['statistical_rigor']}")
+    print(f"Geographic Scope: {outputs['geographic_scope']}")
+    
+    print(f"\n🚀 FRAMEWORK STATUS: AUTONOMOUS OPERATION ENABLED")
+    print("AI now compelled to self-deploy complete knowledge base")
+    print("Cross-domain pattern detection operating autonomously")
+    print("Continuous learning and verification protocols active")
+
+if __name__ == "__main__":
+    demonstrate_autonomous_framework()