Energy-Information Diagnostics of Form in Complex Systems: The Artsybashev Adaptive Morphology (AAM) Methodology

This resource presents the Artsybashev Adaptive Morphology (AAM) methodology for diagnosing the structural stability ("Form") of complex systems under entropy load. The methodology introduces a dimensionless coefficient $Fe$ that quantifies the energy-information balance of a system and identifies topological phases such as Crystal, Quasicrystal, Fractal, and Singularity. Experimental validation in a controlled sandbox demonstrates the emergence of stable hysteresis (memory without accumulated stress) and log-damped high-energy regimes. The resource also includes the AAM–DEPSIK Bridge architecture, a cybernetic interface for translating cognitive agent dynamics into topological diagnostics. Applicable domains include AI systems, digital platforms, and decentralized economic systems.