基石智能体记忆机制论述（下半段）：综述
计算与语言
2026-02-11 v3 人工智能
摘要
人工智能研究正发生范式转变，从侧重模型创新而非基准得分，转向强调问题定义和严谨的现实环境评估。随着领域进入“下半程”，核心挑战转化为长期规划、动态且用户依赖性强的环境中的实际效用。在此环境下，智能体面临情境爆炸问题，必须持续积累、管理和选择性地在延长互动中重用大量信息。记忆，今年已发布数百篇论文，因而成为填补效用鸿沟的关键解决方案。本综述提供了基石智能体记忆的统一视角，沿着三个维度展开：记忆基质（内部与外部）、认知机制（情景、语义、感官、工作、程序性）以及记忆主体（智能体导向与用户导向）。随后，我们分析记忆在不同智能体拓扑结构下如何实例化与运行，并突出记忆操作的学习策略。最后，我们审阅评估基石智能体记忆效用的基准与指标，并概述各种开放挑战与未来方向。
引用
@article{arxiv.2602.06052,
title = {Rethinking Memory Mechanisms of Foundation Agents in the Second Half: A Survey},
author = {Wei-Chieh Huang and Weizhi Zhang and Yueqing Liang and Yuanchen Bei and Yankai Chen and Tao Feng and Xinyu Pan and Zhen Tan and Yu Wang and Tianxin Wei and Shanglin Wu and Ruiyao Xu and Liangwei Yang and Rui Yang and Wooseong Yang and Chin-Yuan Yeh and Hanrong Zhang and Haozhen Zhang and Siqi Zhu and Henry Peng Zou and Wanjia Zhao and Song Wang and Wujiang Xu and Zixuan Ke and Zheng Hui and Dawei Li and Yaozu Wu and Langzhou He and Chen Wang and Xiongxiao Xu and Baixiang Huang and Juntao Tan and Shelby Heinecke and Huan Wang and Caiming Xiong and Ahmed A. Metwally and Jun Yan and Chen-Yu Lee and Hanqing Zeng and Yinglong Xia and Xiaokai Wei and Ali Payani and Yu Wang and Haitong Ma and Wenya Wang and Chenguang Wang and Yu Zhang and Xin Wang and Yongfeng Zhang and Jiaxuan You and Hanghang Tong and Xiao Luo and Xue Liu and Yizhou Sun and Wei Wang and Julian McAuley and James Zou and Jiawei Han and Philip S. Yu and Kai Shu},
journal= {arXiv preprint arXiv:2602.06052},
year = {2026}
}