计算机工程2026，Vol.52Issue(2)：1-6,6.DOI:10.19678/j.issn.1000-3428.0253281
大模型技术演进:世界模型让人工智能从感知走向决策(特邀)
Evolution of Large Model Technologies:World Models Drive Artificial Intelligence from Perception to Decision-Making(Invited)
摘要
Abstract
Large Language Models(LLMs)have propelled artificial intelligence into an era of natural language-centric interaction;however,they remain significantly limited in terms of physical world modeling and complex decision-making.To address these limitations,this paper considers the world model as its core paradigm and systematically analyzes the key technical pathways for the evolution of LLMs into decision-making agents.First,the capability boundaries of LLMs are delineated,highlighting their intrinsic limitations in structured knowledge representation,real-world perception,and applications that require high reliability.Subsequently,the core essence and key characteristics of world models are summarized in terms of dynamic prediction,task-driven selective modeling,multimodal fusion,and physical consistency.Building on this,data-driven generative modeling and physics-prior-driven simulation modeling are systematically reviewed and compared.Additionally,common technical challenges,including acquisition of high-quality interactive data,long-term prediction consistency,unified multimodal representation,and real-time inference efficiency,are analyzed.Furthermore,the potential and limitations of world models in bridging common-sense gaps,enhancing planning and decision-making capabilities,and supporting embodied intelligence on the path toward Artificial General Intelligence(AGI)are discussed.Finally,considering current technological trends,a forward-looking perspective on future research directions,including LLM-world model integration,data and algorithm co-optimization,fusion of physics priors with generative modeling,tight integration with embodied intelligence,and ethical and safety governance,is provided.This paper systematically analyzes the current status and future development of world-model technologies and provides theoretical and practical guidance for advancing artificial intelligence from perception-to decision-driven capabilities.关键词
世界模型/大语言模型/通用人工智能/多模态感知/决策规划/具身智能Key words
world model/Large Language Model(LLM)/Artificial General Intelligence(AGI)/multimodal perception/decision-making and planning/embodied intelligence分类
信息技术与安全科学引用本文复制引用
王利民,朱光辉,吴涛..大模型技术演进:世界模型让人工智能从感知走向决策(特邀)[J].计算机工程,2026,52(2):1-6,6.基金项目
科技创新2030—"新一代人工智能"重大项目(2022ZD0160900) （2022ZD0160900）
江苏省自然科学基金攀登项目(BK20250009). （BK20250009）
