A Computation Model Based on Consciousness

Abstract

This paper proposes a novel computational model for exploring the nature of consciousness, moving beyond purely objective data-driven approaches. The core claim centers on constructing a model grounded in an individual's consciousness state and subjective experience. This is achieved through the utilization of brain-computer interface (BCI) technology to capture signals indicative of consciousness, which are then mapped and processed within the model. The research investigates the potential for consciousness to be a fundamental element in computation, offering a new perspective for the development of intelligent systems capable of possessing subjective awareness. The model presented here utilizes a multi-layered architecture incorporating information theory principles, Bayesian inference, and dynamical systems theory to represent and simulate conscious experience. Key elements include a 'Qualia Vector' representing subjective sensory qualities, a 'Contextual Awareness Matrix' capturing environmental and internal state influences, and a 'Predictive Resonance Network' modelling the dynamic interplay between perception, action, and self-awareness. The model's efficacy will be evaluated through simulations and theoretical analysis, demonstrating the potential for capturing key aspects of conscious experience such as attention, intention, and emotional states. ---