Abstract Functional Language Logic: A Competitive Mixture of Experts Architecture for Paradox-Free Reasoning and Adaptive Intelligence

The prevailing paradigm of Large Language Models (LLMs) relies heavily on probabilistic next-token prediction. While this yields impressive linguistic fluency, it fundamentally struggles with strict logical deduction, often succumbing to semantic hallucinations, linguistic paradoxes, and high computational latency. This paper introduces a radical departure from probabilistic text-based reasoning: the Competitive Mixture of Experts (CMoE) framework based on Functional Language Logic (FLL). We propose offloading the "thinking" process from massive, opaque linguistic transformers to a highly efficient, dedicated cognitive engine built entirely upon mathematical functional approximators (linear, parabolic, and…