多粒度认知智能计算研究综述
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国家重点研发计划项目(No.2021YFF07041000);国家自然科学基金——专项基金(No.62221005)、重点项目(No.61936001)、面上项目(No.62376045);重庆市自然科学基金(No.cstc2021ycjh-bgzxm0013);重庆市教育委员会重点合作项目(No.HZ2021008)


Survey for Research on MultiGranularity Cognitive Intelligent Computing
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    摘要:

    认知计算与粒计算是从不同视角模拟人脑认知机制以构建智能计算模型的有效方法。多粒度认知智能计算融合了这2种计算模式的优势,旨在整合人脑认知与信息处理这2种看似矛盾的机制,从而构建出鲁棒、高效且可解释的智能计算模型。本文首先围绕解决不确定性问题的理论与方法,回顾了经典的多粒度认知计算模型,并介绍了最新的研究进展;接着,从粒化与认知的视角,阐述了当前多粒度认知智能计算理论及其应用的研究进展。最后,分析并展望了多粒度智能计算中亟待研究的重要问题。

    Abstract:

    Cognitive computing and granular computing are effective approaches for simulating the cognitive mechanisms of the human brain from different perspectives to construct intelligent computing models. Multigranularity cognitive intelligent computing integrates the advantages of these two computing paradigms, aiming to integrate the seemingly contradiction mechanisms between the processes of human cognitive and information processing, thereby constructing computing models with robust, efficient, and interpretable intelligent. It first summarizes classical multigranularity cognitive computing models about addressing uncertainty issues and their latest research advancements. Furthermore, the current research progress on multigranularity cognitive intelligent computing theory and its applications are elaborated from the perspectives of granulation and cognition. Finally, important issues that urgently need to be studied in multigranularity intelligent computing are analyzed and discussed.

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王国胤,吴成英.多粒度认知智能计算研究综述[J].重庆师范大学学报自然科学版,2024,41(4):1-12

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  • 在线发布日期: 2024-10-22