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面向复杂系统理解与管控的认知仿真方法
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科技导报 | 专题论文 2018,36(12): 55-65
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科技导报 |专题论文 2018 , 36 (12) : 55 -65
面向复杂系统理解与管控的认知仿真方法
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陶九阳1,2, 吴琳1, 胡晓峰1, 贺筱媛1
作者信息
    1. 国防大学联合作战学院, 北京 100091;
    2. 陆军工程大学指挥控制工程学院, 南京 210007
作者简介:
陶九阳,博士研究生,研究方向为战争模拟、复杂系统、军事运筹与智能决策,电子信箱:taojiuyang@126.com
Cognitive simulation for complex system understanding and management
  • TAO Jiuyang1,2, Wu Lin1, HU Xiaofeng1, HE Xiaoyuan1
  • Affiliations
      1. Joint Operations College, National Defense University, Beijing 100091, China;
      2. Command and Control Engineering College, Army Engineering University of PLA, Nanjing 210007, China
    出版时间: 2018-06-28 doi: 10.3981/j.issn.1000-7857.2018.12.008
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    概述了复杂性科学的兴起与发展历程,论述了复杂系统的主要研究方法,以及复杂系统难以理解和管控的根源;分析了认知智能的突破性进展与关键技术;提出了面向复杂系统理解和管控的认知仿真方法,以及认知仿真的基本理念;指出了目前认知仿真研究中存在的问题和不足。
    认知仿真  /  深度强化学习  /  复杂系统  /  复杂性  /  认知智能
    The rise and the development of the complexity science are reviewed. The concepts of the uncertainty, the adaptability and the emergence of the complex systems are analyzed, as well as the main research methods, and the source of difficulties in their understanding and control. The breakthroughs and the key technologies of the cognitive intelligence are summarized, together with the basic concepts of the cognitive simulation. Finally, the existing problems and shortcomings of the cognitive simulation are outlined.
    cognitive simulation  /  deep reinforcement learning  /  complex systems  /  complexity  /  cognitive intelligence
    陶九阳, 吴琳, 胡晓峰, 贺筱媛. 面向复杂系统理解与管控的认知仿真方法. 科技导报, 2018 , 36 (12) : 55 -65 . DOI: 10.3981/j.issn.1000-7857.2018.12.008
    TAO Jiuyang, Wu Lin, HU Xiaofeng, HE Xiaoyuan. Cognitive simulation for complex system understanding and management[J]. Science & Technology Review, 2018 , 36 (12) : 55 -65 . DOI: 10.3981/j.issn.1000-7857.2018.12.008

      军民共用重大研究计划联合基金项目(U1435218);国家自然科学基金项目(61403400,61403401)

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    doi: 10.3981/j.issn.1000-7857.2018.12.008
    • 接收时间:2018-04-03
    • 首发时间:2018-06-21
    • 出版时间:2018-06-28
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    • 收稿日期:2018-04-03
    • 修回日期:2018-05-11
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    属数
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    species
    占总种数比例
    Percentage of
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    Genus
    种数
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    species
    占总种数比例
    Percentage of total
    species (%)
    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
    光柄菇属 Pluteus 5 2.39
    红菇属 Russula 17 8.13
    栓菌属 Trametes 5 2.39
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