Architecting Quantum Computational Model for Brain Inspired Adaptive English Language Acquisition

Abstract

The merger of quantum computation with cognitive neuroscience presents a profound opportunity to rethink the fundamentals of English language acquisition systems. Present day adaptive learning technologies predicated on symbolic AI, machine learning and deep neural networks are confined to classical computing paradigms that narrow down language learning to conventional optimisation, neglecting the contextual, probabilistic and evolving behaviour of human brain. This paper proposes a model for Brain inspired adaptive English language acquisition that combines ideas from quantum computation, neural networking and adaptive learning into a well structured architecture. The model adapts four interconnected layers: Layer of quantum cognition for the process of decoding language states as quantum superpositions an adaptive semantic network. a neural symbolic interface. a dynamic learner pathway