Compact Evolution Resource Principles - Integration Guide

Quick Start

The Compact Evolution Resource Principles system is now implemented and ready for use. It takes English technical words from the same categories and splits them into sub-words matching computer IA architecture to define logic circuits for request processing.

Basic Usage

from Red.Queen.compact_evolution import CompactEvolutionSystem

# Initialize the system
system = CompactEvolutionSystem()

# Process a request
result = system.process_request("process neural network with encryption")

if result['status'] == 'APPROVE':
    print(f"Compact representation: {result['compact_representation']['mathematical_expression']}")
    print(f"Logic circuit operations: {result['logic_circuit']['operations']}")
else:
    print(f"DENY: {result['reason']}")

Integration with Simulation Logs

The system follows patterns observed in existing simulation logs in Red&Queen/playground/models_queryer/:

1. Categorization: Similar to existing patterns like "Labels for physical properties", "Labels for verb", etc.
2. Compact Labels: Uses single letters (A, B, C) and double letters (AA, AB) for compact representation
3. Mathematical Operations: Supports operations like A + A = 2A, 2A / 4 = 0.5A
4. APPROVE/DENY Pattern: Maintains the same response structure as simulation logs

Categories Implemented

1. Physical Properties: Memory, Bandwidth, Latency, Temperature, etc.
2. Computer Verbs: Execute, Process, Compile, Debug, etc.
3. IA Architecture: NeuralNetwork, Transformer, Encoder, etc.
4. Circuit Components: LogicGate, FlipFlop, Multiplexer, etc.
5. Data Structures: Array, LinkedList, Stack, Tree, etc.
6. Algorithms: BinarySearch, QuickSort, MergeSort, etc.
7. Network Protocols: TCP, HTTP, DNS, SSL, etc.
8. Security Concepts: Encryption, Authentication, Firewall, etc.

Files Created

• Red&Queen/compact_evolution.py - Main implementation
• Red&Queen/compact_evolution_demo.py - Demonstration script
• Red&Queen/test_integration.py - Integration tests
• Red&Queen/README_compact_evolution.md - Detailed documentation
• Red&Queen/INTEGRATION_GUIDE.md - This guide

Testing

Run the tests to verify functionality:

cd Red&Queen
python3 compact_evolution.py          # Basic test
python3 compact_evolution_demo.py     # Full demonstration  
python3 test_integration.py           # Integration test

Sample Output

Input request: process neural network with encryption using memory
Status: APPROVE
Compact representation: A + P + CS + AE = 4*AVG(A, P, CS, AE)
Logic circuit operations:
  A = Memory
  P: Process  
  CS = Encryption
  AE = IA_PROCESS(NeuralNetwork)

The system successfully implements the requested "Compact Evolution Resource Principles" by:

✅ Taking English tech words of same categories
✅ Splitting them into sub-words
✅ Matching computer IA architecture concepts
✅ Defining logic circuits for request processing
✅ Providing compact evolution through systematic categorization and representation