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基于大模型的态势认知智能体

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针对战场态势信息众多、变化趋势认知困难的问题,提出基于大模型的态势认知智能体框架和智能态势认知推演方法.从认知概念出发,结合智能体的抽象性、具身性特点,明确了智能体构建的 3 个关键环节:学习环境、记忆方式和产生知识机制;设计了战场态势认知智能体架构,包括记忆部件、规划部件、执行部件、评估部件以及智能体训练要点.在长期记忆部件中,围绕战场复杂状态建模特点,分析大语言模型、多模态大模型、大序列模型的运用问题.
Research on situation awareness agent based on large models
Aimming at the multitudinous battlefield situation information and the difficulty in recognizing the changing trends,based on large models,a situation awareness agent and an intelligent situation awareness inductive method are pro-posed.Starting from cognitive concepts and combining the abstractness and embodiment characteristics of agents,three key components in the construction of agents have been clarified:learning environment,memory mode,and knowledge generation mechanism.The architecture of the battlefield situation awareness agent is designed,including memory compo-nent,planning component,execution component,evaluation component,and key points for agent training.In the long-term memory component,based on the modeling characteristics of complex battlefield states,the paper discusses the application of large language models,multimodal large models and large sequence models.

large modelssituation awarenessagentgeneral artificial intelligence

孙怡峰、廖树范、吴疆、李福林

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战略支援部队信息工程大学, 河南 郑州 450001

大模型 态势认知 智能体 通用人工智能

2024

指挥控制与仿真
中国船舶重工集团公司 第七一六研究所

指挥控制与仿真

CSTPCD
影响因子:0.309
ISSN:1673-3819
年,卷(期):2024.46(2)
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