Symmetry-Fractal Heuristic Method: Unified Framework Document

This document summarizes the development and testing of a novel heuristic framework called the Symmetry-Fractal Heuristic Method. The core innovation replaces conventional static equality ($=$) with a Line of Symmetry (LOS) as the foundational starting point for problem exploration. The method maintains openness in the solution space as long as possible, reduces complexity to binary (If/Or) choices, and then fractalizes the remaining possibilities through self-similar iteration across multiple scales. The path that produces the most robust, stable, and self-similar structure is selected as the preferred solution. Asymmetry is deliberately introduced as a diagnostic tool to reveal why alternative paths fail (e.g., fragmentation, drift, or scale instability). Hidden Variables (HV) are incorporated to represent underlying structures not immediately visible. Additional dynamic features include real-time iteration mapping, a "Drop Rule" for analyzing sudden state changes, and range operators for constraining outputs. The framework has been tested extensively on both solved and open problems in mathematics and physics, recovering known correct answers on solved problems and providing clear, intuitive signals on open problems. The framework demonstrates originality as a unified heuristic tool that blends geometric intuition, recursion, diagnostics, and adaptive learning.