太极统一场论驱动的下一代世界模型:从概率预测走向伟人级战略趋势研判 Research on Next-Generation World Model Driven by Taiji Unified Field Theory: From Probabilistic Prediction to Great Man-Level Strategic Trend Deduction

当前大语言模型与世界模型深陷“无约束概率生成”的泥潭,缺乏对全局因果的把握,极易产生“幻觉”,且无法预判系统的长期趋势。本文突破西方以数据拟合为基础的架构,提出一种基于太极统一场论(TUFT)的新型认知世界模型。该模型将现实态势映射为“阳场(动能/目标)”与“阴场(阻力/风险)”,引入“权衡变量K”作为内生状态。通过八大规律(对立统一、阴阳流转、一体两面、量变质变、循环往复、同频共振、相反相成、相辅相成)构建算法逻辑,系统能够自发推演“战略进攻(K>1)”、“战略相持(-1≤K≤1)”与“战略防御(K<-1)”三大模态。在轻量级Web仿真中,该模型成功实现了基于势差的战略预见与态势分岔。本研究为人工智能赋予了“伟人级”的宏观预见力与辩证思维,为消除AI幻觉、构建可解释、可演化的通用人工智能(AGI)提供了全新的物理与哲学范式。 Abstract Current Large Language Models (LLMs) and World Models are trapped in the dilemma of "unconstrained probabilistic generation." They lack a grasp of global causality, are highly prone to "hallucinations," and cannot predict the long-term trends of a system. Breaking through the Western architecture based on data fitting, this paper proposes a novel cognitive World Model based on the Taiji Unified Field Theory (TUFT). The model maps real-world situations into a "Yang Field (kinetic energy/goals)" and a "Yin Field (resistance/risks)," introducing a "trade-off variable K" as an endogenous state. By constructing algorithmic logic through the Eight Laws (Unity of Opposites, Yin-Yang Flow, Two Sides of One Body, Quantitative to Qualitative Change, Cyclical Repetition, Resonance, Mutual Opposition and Complementarity), the system can spontaneously deduce three major modes: "Strategic Offensive (K>1)," "Strategic Stalemate (-1<=K<=1)," and "Strategic Defensive (K<-1)." In lightweight Web simulations, the model successfully achieved strategic foresight and bifurcation based on potential differences. This research endows AI with "Great Man-level" macroscopic foresight and dialectical thinking, providing a new physical and philosophical paradigm for eliminating AI hallucinations and building explainable, evolvable Artificial General Intelligence (AGI).