“人-机结合”的综合集成研讨体系

doi:10.16451/j.cnki.issn1003-6059.202209001

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摘要 “综合集成研讨体系”属于系统科学的基础理论层次,是开放的复杂巨系统的方法论,同时也是思维科学的一项应用技术,属于思维科学的工程应用层次,是系统科学与思维科学交叉发展产生的原创性成果.文中从系统科学和思维科学两方面阐述综合集成研讨体系提出的理论背景.从思维与智能的进化角度,提出人-机结合的三个层次.从思维科学的视角,探究了“综合集成研讨厅”平台提升思维能力、实现“人-机智能”增强的途径,试图对复杂问题求解和人-机融合智能共进有所启示.综合集成研讨体系对群体思维、机器智能和知识体系综合运用,激发个体思维→个体智慧→群体智慧→社会智慧的演进过程.从思维科学、信息科学与技术、网络技术结合的智能科学,到体现人文科学与自然科学相互交叉与融合的社会智能科学,这一历程中渗透着钱学森前瞻性的科学思想与博大精深的智慧.

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	郑楠
	章颂
	戴汝为

关键词 ：综合集成研讨体系(HWME), 思维科学, 复杂系统, 人-机结合, 群体思维

Abstract：Hall for workshop of metasynthetic engineering (HWME) belongs to the basic theoretical level of system science, which is a methodology of open complex giant systems (OCGSs). It is also an application technology of noetic science, which belongs to the engineering application level of noetic science, and is an original result of the cross development of system science and noetic science. This paper expounds the theoretical background of HWME from the aspects of system science and noetic science. From the perspective of the evolution of noetic and intelligence, three levels of man-machine integration are proposed. From the perspective of noetic science, this paper explores the ways to improve the thinking ability of HWME and realize the enhancement of human-machine intelligence, and tries to enlighten the complex problem solving and man-machine integration intelligence. Group thinking, machine intelligence and knowledge system are applied in HWME to stimulate the evolution process of individual thinking → individual wisdom → group wisdom → social wisdom. From the intelligent science that combines noetic science, information science and technology, and network technology to the social intelligent science that reflects the intersection and integration of humanities and natural science, Mr. Qian Xuesen's forward-looking scientific thoughts and broad and profound wisdom permeate this process.

Key words： Hall for Workshop of Metasynthetic Engineering(HWME) Noetic Science Complex System Man-Machine Integration Group Thinking

收稿日期: 2022-06-28

ZTFLH:

TP 399

基金资助:中国科学院自动化研究所基础科研项目(No.Y9J2FZ0801)、中国科学院战略性先导科技专项项目(No.XDA27000000)资助

通讯作者: 郑楠,博士,副研究员,主要研究方向为复杂系统、综合集成、数据挖掘、机器学习.E-mail:nan.zheng@ia.ac.cn.

作者简介: 章颂,博士研究生,主要研究方向为复杂系统、综合集成、数据挖掘、机器学习.E-mail:zhangsong2022@ia.ac.cn. 戴汝为,研究员.主要研究方向为复杂系统、综合集成、模式识别.E-mail:ruwei.dai@ia.ac.cn.

引用本文:

郑楠, 章颂, 戴汝为. “人-机结合”的综合集成研讨体系[J]. 模式识别与人工智能, 2022, 35(9): 767-773. ZHENG Nan, ZHANG Song, DAI Ruwei. Hall for Workshop of Metasynthetic Engineering Based on Man-Machine Integration. Pattern Recognition and Artificial Intelligence, 2022, 35(9): 767-773.

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http://manu46.magtech.com.cn/Jweb_prai/CN/10.16451/j.cnki.issn1003-6059.202209001 或 http://manu46.magtech.com.cn/Jweb_prai/CN/Y2022/V35/I9/767

[1] KOVARIK C, LEE I, KO J, et al. Commentary: Position Statement on Augmented Intelligence(AuI). Journal of the American Academy of Dermatology, 2019, 81(4): 998-1000.
[2] DELLERMANN D, EBEL P, SÖLLNER M, et al. Hybrid Intelli-gence. Business and Information Systems Engineering, 2019, 61(5): 637-643.
[3] KANTOSALO A, TOIVONEN H.Modes for Creative Human-Computer Collaboration: Alternating and Task-Divided Co-creativity // Proc of the 7th International Conference on Computational Creativity. Washington, USA: IEEE, 2016: 77-84.
[4] MCCAFFREY T, SPECTOR L.An Approach to Human-Machine Collaboration in Innovation. Artificial Intelligence for Engineering Design Analysis and Manufacturing, 2018, 32(1): 1-15.
[5] ENGELBART D C.Augmenting Human Intellect: A Conceptual Fra-mework[C/OL]. [2022-05-21].https://www.dougengelbart.org/content/view/138.
[6] SILVER D, HUANG A, MADDISON C J, et al. Mastering the Game of Go with Deep Neural Networks and Tree Search. Nature, 2016, 529(7587): 484-489.
[7] 戴汝为. 从定性到定量的综合集成法的形成与现代发展.自然杂志, 2009, 31(6): 311-314, 326.
(DAI R W.The Proposal and Recent Development of Metasynthetic Method(M) from Qualitative to Quantitative. Chinese Journal of Nature, 2009, 31(6): 311-314, 326.)
[8] 钱学森,于景元,戴汝为.一个科学新领域——开放的复杂巨系统及其方法论.自然杂志, 1990, 13(1): 3-10.
(QIAN X S, YU J Y, DAI R W.A New Field of Science-Open Complex Giant System and Its Methodology. Chinese Journal of Nature, 1990, 13(1): 3-10.)
[9] 王丹力,郑楠,刘成林.综合集成研讨厅体系起源、发展现状与趋势.自动化学报, 2021, 47(8): 1822-1839.
(WANG D L, ZHENG N, LIU C L.Hall for Workshop of Metasynthetic Engineering: The Origin, Development Status and Future.Acta Automatica Sinica, 2021, 47(8): 1822-1839.)
[10] KNEBEL D, AYALI A, GUERSHON M, et al. Intra-Versus Intergroup Variance in Collective Behavior. Science Advances, 2019, 5(1). DOI: 10.1126/sciadv.aav0695.
[11] CULHA U, DAVIDSON Z S, MASTRANGELI M, et al. Statistical Reprogramming of Macroscopic Self-Assembly with Dynamic Boundaries. Proceedings of the National Academy of Sciences of the United States of America, 2020, 117(21): 11306-11313.
[12] 戴汝为,李耀东.基于综合集成的研讨厅体系与系统复杂性.复杂系统与复杂性科学, 2004, 1(4): 1-24.
(DAI R W, LI Y D.Researches on Hall for Workshop of Metasynthetic Engineering and System Complexity. Complex Systems and Complexity Science, 2004, 1(4): 1-24.)
[13] 戴汝为. “再谈开放的复杂巨系统” 一文的影响.模式识别与人工智能, 2001, 14(2): 129-134.
(DAI R W.The Influence of Qian's Talk on "Open Complex Giant Systems". Pattern Recognition and Artificial Intelligence, 2001, 14(2): 129-134.)
[14] JACKSON P C.Introduction to Artificial Intelligence. 3rd Edition. New York, USA: Dover Publications, 2019.
[15] SILVER D, HUBERT T, SCHRITTWIESER J, et al. Mastering Chess and Shogi by Self-Play with a General Reinforcement Lear-ning Algorithm[C/OL].[2022-05-21]. https://arxiv.org/pdf/1712.01815.pdf.
[16] 卢明森. 钱学森与思维科学.中国工程科学, 2002, 4(2): 8-15.
(LU M S.Qian Xuesen and Noetic Science. Engineering Science, 2002, 4(2): 8-15.)
[17] 卢明森. 钱学森对思维科学的卓越贡献——纪念钱学森院士归国 60 周年 // 钱学森研究(第1辑). 上海:上海交通大学出版社, 2016: 91-109.
(LU M S.Qian Xuesen's Outstanding Contribution to Noetic Science-In Memory of the 60th Anniversary of the Return of Academician Qian Xuesen // Qian Xuesen's Research(Volume 1). Shanghai, China: Shanghai Jiao Tong University Press, 2016: 91-109.)
[18] ZHU W J.Model Checking for AlphaCode-Generated Programs // Proc of the 7th International Conference on Intelligent Computing and Signal Processing. Washington, USA: IEEE, 2022: 794-798.
[19] ZHANG T L, CHENG X, JIA S C, et al. Self-Backpropagation of Synaptic Modifications Elevates the Efficiency of Spiking and Artificial Neural Networks. Science Advances, 2021, 7(43). DOI: 10.1126/sciadv.abh0146.
[20] ZHANG Y H, QU P, JI Y, et al. A System Hierarchy for Brain-Inspired Computing. Nature, 2020, 586(7829): 378-384.
[21] 赵光武. 钱学森给戴汝为的信 // 赵光武.思维科学研究.北京: 中国人民大学出版社, 1999: 605.
(ZHAO G W.Letter from Qian Xuesen to Dai Ruwei // ZHAO G W. Noetic Science Research. Beijing, China: Renmin University Press, 1999: 605.)
[22] KUHN T S.The Structure of Scientific Revolutions. Chicago, USA: University of Chicago Press, 1996.
[23] WARFIELD J N.Spreadthink: Explaining Ineffective Groups. Systems Research, 1995, 12(1): 5-14.
[24] 戴汝为,李耀东,李秋丹.社会智能与综合集成系统.北京:人民邮电出版社, 2013.
(DAI R W, LI Y D, LI Q D.Social Intelligence and Metasynthe-tic System. Beijing, China: Posts and Telecom Press, 2013.)