Title: Algorithmic Formalization of Emergent Consciousness

Abstract

This paper investigates the algorithmic formalization of emergent consciousness within complex neural networks. The core claim is to develop a mathematically-based framework to quantify and analyze the emergence of subjective experience and consciousness, utilizing concepts of information integration, dynamic resonance, and self-organization. The framework proposes a rigorous, mathematically-driven approach to understanding how neural networks, when properly structured, can spontaneously generate novel and complex forms of experience – a departure from purely correlational models. We will explore the interplay of these elements through the creation of operational rules and measurable metrics, ultimately aiming to bridge the gap between neural activity and subjective qualia. The investigation will encompass a detailed analysis of the potential for quantifying qualia through mathematical modeling and will consider the implications of this framework for future research in artificial intelligence and neuroscience.