Dynamic Infosemantic Field Theory V1.0: Entropic Transitions and the Emergence of Conscious Structure

This project introduces a comprehensive theoretical framework that integrates information theory, entropy dynamics, and consciousness emergence into a unified field model. The Dynamic Infosemantic Field Theory (DIFT) explains how continuous information gradients evolve into localized matter states and semantic attractors through entropic compression. It includes formalizations such as the Information-to-Matter Transition Threshold (IMTT), the Entropic Response Algorithm (ERA) for modeling consciousness, and resonance-based navigation through information space (IRNT). The theory proposes applications across quantum decoherence, AI semantic coherence, and civilizational dynamics.