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p235

This repository contains collections of design patterns and organizational metaphors with formal specifications.

📖 Documentation

Formal Specifications

  • Formal Specification Summary - Complete overview of architecture and Z++ specifications
  • docs/ - Comprehensive technical documentation (2,328 lines)
    • Architecture overview with Mermaid diagrams
    • Z++ formal specifications (data model, system state, operations, integrations)
    • Usage guide for specifications

Pattern Collections

  • APL: Christopher Alexander's "A Pattern Language" (253 patterns) - architectural and urban design patterns
  • UIA: Union of International Associations "Patterns & Metaphors" (253 patterns) - organizational and conceptual patterns

Markdown Versions

The markdown/ directory contains converted versions of all APL and UIA pages in markdown format for improved readability and accessibility:

  • markdown/apl/: 253 A Pattern Language patterns (apl001.md - apl253.md)
  • markdown/uia/: 253 UIA Patterns & Metaphors (12610010.md - 12612530.md)
  • markdown/arc/: 102 Archetypal Patterns extracted from UIA templates with domain-specific placeholders

See markdown/README.md for detailed information about the conversion process and markdown structure.

Pattern Language Schema

The repository includes formalized JSON schemas for both the Pattern Language and Archetypal Patterns:

APL Pattern Language Schema

  • Pattern Language Schema (pattern_language_generated.json) - Complete meta-pattern, categories, and sequences
  • Pattern Sequences (pattern_sequences.json) - All 36 pattern sequences with emergent phenomena
  • Categories (category_*.json) - Towns, Buildings, and Construction categories

See PATTERN_SCHEMA_README.md for detailed information about the APL schema structure.

Archetypal Pattern Schema

  • Archetypal Pattern Schema (archetypal_pattern_schema.json) - JSON schema for archetypal patterns
  • Archetypal Patterns (archetypal_patterns.json) - All 102 archetypal patterns with domain mappings
  • Placeholder Reference (archetypal_placeholders.json) - Complete placeholder documentation

Archetypal patterns use the format: "generic {{domain-specific}} generic" and can be transformed across:

  • Physical - Spatial, material, architectural domains
  • Social - Organizational, community, institutional domains
  • Conceptual - Knowledge, theoretical, paradigmatic domains
  • Psychic - Awareness, consciousness, mental domains

See ARCHETYPAL_SCHEMA_README.md for detailed information about the archetypal pattern schema.

Generating Schemas

# Generate APL Pattern Language schema
python3 generate_pattern_schema.py

# Generate Archetypal Pattern schema
python3 generate_archetypal_schema.py

Testing Schemas

# Test APL schema (if tests exist)
python3 validate_schema.py

# Test Archetypal schema
python3 test_archetypal_schema.py

Demo Schemas

# Demo APL schema
python3 demo_pattern_schema.py

# Demo Archetypal schema
python3 demo_archetypal_schema.py

OpenCog Atomese Representation

The Pattern Language has been converted to OpenCog's Atomese format for knowledge representation and pattern matching:

  • opencog_atomese/ - Complete Atomese hypergraph representation in Scheme format
    • pattern_language.scm - Complete representation
    • meta_pattern.scm - Meta-pattern
    • categories.scm - Categories with InheritanceLinks
    • sequences.scm - Sequences with MemberLinks
    • Enhanced Features:
      • pattern_language_enhanced.scm - Enhanced with diagrams, details, and connections
      • relationship_types.scm - Pattern relationship types (complement, conflict, alternative)
      • patterns/ - Individual .scm files for modular loading

The Atomese format enables:

  • Pattern matching and reasoning in OpenCog
  • Hypergraph queries for pattern relationships
  • Knowledge graph navigation and inference
  • Integration with AI/AGI systems

See opencog_atomese/README.md for usage examples and opencog_atomese/ENHANCEMENTS.md for enhanced features documentation.

Generating Atomese Files

# Generate base Atomese files
python3 generate_opencog_atomese.py

# Generate enhanced features
python3 generate_enhanced_atomese.py

Testing Atomese Files

# Test base files
python3 test_opencog_atomese.py

# Test enhanced features
python3 test_enhanced_atomese.py

Demo Enhanced Features

python3 demo_enhanced_atomese.py

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