人工智能的跨学科融合：四象模型的理论框架与应用实践

EasyChair Preprint 15958

Abstract

本文提出一种跨学科的人工智能集成框架——"四象模型"，通过文科AI的符号涌现、理科AI的规律发现、工科AI的物理映射以及认知协同的流形跃迁，实现符号系统与物理世界的深度耦合。本文详细解析各分支的核心数学模型，论证其物理意义与应用潜力，通过法律文书生成、蛋白质折叠预测等实例验证模型有效性。研究揭示，认知流形方程与量子相变判据为跨模态智能系统提供统一的理论基础，推动人工智能从单一领域工具向通用智能系统演进。

Keyphrases: Artificial intelligence integration framework, Evolution of general-purpose intelligent systems, Manifold transition in cognitive synergy, Pattern discovery in science AI, Physical mapping in engineering AI, Symbolic emergence in liberal arts AI

@booklet{EasyChair:15958,
  author    = {Xiaohui Zou},
  title     = {Interdisciplinary Integration of Artificial Intelligence: Theoretical Framework and Application Practices of the Four-Phase Model},
  howpublished = {EasyChair Preprint 15958},
  year      = {EasyChair, 2025}}