科技评论

人工智能学科体系的构建与探讨

  • 蔡自兴 , 1, 2 ,
  • 蔡昱峰 1, 3
展开
  • 1. 湘江实验室, 长沙 410205
  • 2. 中南大学人工智能与机器人学研究所, 长沙 410083
  • 3. 湖南自兴智慧医疗科技有限公司, 长沙 410013

蔡自兴,教授,研究方向为人工智能等,电子信箱:

收稿日期: 2024-05-13

  网络出版日期: 2025-06-05

基金资助

湘江实验室开放课题(22XJ02005)

湖南省自然科学基金项目(2023JJ60491)

国家工业和信息化部人工智能与实体经济深度融合创新项目

版权

版权所有,未经授权,不得转载。

Construction and exploration of the discipline system of artificial intelligence

  • Zixing CAI , 1, 2 ,
  • Yufeng CAI 1, 3
Expand
  • 1. Xiangjiang Laboratory, Changsha 410205, China
  • 2. Center for Artificial Intelligence and Robotics, Central South University, Changsha 410083, China
  • 3. Hunan Zixing Smart Medical Technology Co., Ltd., Changsha 410013, China

Received date: 2024-05-13

  Online published: 2025-06-05

Copyright

All rights reserved. Unauthorized reproduction is prohibited.

摘要

探讨了人工智能的学科体系,从人工智能的定义出发,提出人工智能的学科体系是由人工智能的科学基础、人工智能技术方法和人工智能应用3部分组成,并认为人工智能的科学基础是符号主义、连接主义和行为主义,人工智能的主要技术是基于知识的人工智能技术、基于数据的人工智能技术、人工智能的算法和人工智能的算力,而人工智能的技术要素为知识、数据、算法和算力,人工智能的应用领域涉及经济、科技、民生、社会和其他领域。

本文引用格式

蔡自兴 , 蔡昱峰 . 人工智能学科体系的构建与探讨[J]. 科技导报, 2025 , 43(8) : 15 -26 . DOI: 10.3981/j.issn.1000-7857.2024.05.00504

1
Turing A A . Computing machinery and intelligence[J]. Mind, 1950, 59: 433- 460.

2
Stuart R , Peter N . Artificial intelligence: A modern approach[M]. New jersey: Prentice-Hall, Inc., 1995.

3
Padhy N P . Artificial intelligence and intelligent systems[M]. New Delhi: Oxford University Press, 2005.

4
蔡自兴, 刘丽珏, 陈白帆, 等. 人工智能及其应用[M]. 7版 北京: 清华大学出版社, 2024.

5
Nilsson N J . Artificial Intelligence: A new synthesis[M]. San Francisco, Calif: Morgan Kaufmann Publishers, 1998.

6
Bellman R E . An introduction to artificial intelligence: Can computers think?[M]. San Francisco: Boyd & Fraser Pub. Co., 1978.

7
Haugeland J . Artificial intelligence: The very deas[M]. Cambridge, Macssachusetts: MIT Press, 1985.

8
Kurzwell R . The age of intelligent machines[M]. Cambridge, Macssachusetts: MIT Press, 1990.

9
Rich E , Knight K . Artificial intelligence[M]. 2nd ed New York: McGraw-Hill, 1991.

10
Dean T , Wellman M P . Planning and control[M]. Santa Barbara: Morgan Kaufmann, 1991.

11
Charniak E , McDermott D V . Introduction to artificial intelligence[M]. Reading, Macssachusetts: Addison- Wesley, 1985.

12
Winston P H . Artificial intelligence[M]. 3rd ed Massachusetts: Addi-son Wesley, 1992.

13
Schalkoff R J . Artificial intelligence: An engineering approach[M]. New York: McGraw-Hill, 1990.

14
Luger G F , Stubblefield W A . Artificial intelligence: Structures and strategies for complex problem solving[M]. 2nd ed California: Benjamin/Cummings, 1993.

15
傅京孙, 蔡自兴, 徐光祐. 人工智能及其应用[M]. 北京: 清华大学出版社, 1987.

16
蔡自兴. 人工智能学派及其在理论、方法上的观点[J]. 高技术通讯, 1995, 5(5): 55- 57.

DOI

17
Gu F H . Recent developments in the EU and US brain research programs[J]. Science, 2014, 66(5): 16- 21.

18
Rumelhart D E, Hinton G E, Williams R J. Learning internal representations by error propagation [M]//Rumelhart D E, McClelland J L. Parallel Distributed Processing. Cambridge, Massachusetts: MIT Press, 1986.

19
Brooks R A . Symbolic reasoning among 3-D models and 2-D images[J]. Artificial Intelligence, 1981, 17: 285- 348.

DOI

20
李德毅. 论智能的困扰和释放[J]. 智能系统学报, 2024, 19(1): 249- 257.

21
蔡自兴, 徐光祐. 人工智能及其应用[M]. 2版 北京: 清华大学出版社, 1996.

22
蔡自兴, 陈爱斌. 人工智能辞典[M]. 北京: 化学工业出版社, 2008.

23
Cai Z X , Liu L J , Chen B F , et al. Artificial intelligence: From begin-ning to date[M]. Singapore: World Scientific Publishers, 2020.

24
Fu K . Learning control systems and intelligent control systems: An inter-section of artifical intelligence and automatic control[J]. IEEE Transactions on Automatic Control, 1971, 16(1): 70- 72.

DOI

25
Saridis G N . Toward the realization of intelligent controls[J]. IEEE Proceedigs, 1979, 67(8): 1115- 1133.

DOI

26
蔡自兴. 智能控制[M]. 北京: 电子工业出版社, 1990.

27
Cai Z X . Intelligent control: Principles, techniques and applications[M]. Singapore: World Scientific, 1997.

28
蔡自兴. 智能控制学科体系的初步框架[C]//1998年中国智能自动化学术会议. 上海: 中国自动化学会, 1998: 45-48.

29
蔡自兴. 智能控制导论[M]. 4版 北京: 中国水利水电出版社, 2024.

30
蔡自兴, 贺汉根. 智能科学发展若干问题[J]. 自动化学报, 2002, 28(增刊): 142- 150.

31
Cai Z X. Intelligence science: Disciplinary frame and general features [C]//Proceedings of IEEE International Conference on Robotics, Intelligent Systems and Signal Processing (RISSP). Changsha, 2003: 393-398.

32
National Science and Technology Council, Networking and Information Technology Research and Development Subcommittee. The national artificial intelligence research and development strategic plan[EB/OL]. (2016-10-13)[2025-03-18]. https://www.nitrd.gov/PUBS/national_ai_rd_strategic_plan.pdf.

33
蔡自兴. 智能科学学科若干问题的讨论[J]. 计算机教育, 2017(10): 6- 8.

DOI

34
Mariani M M , Machado I , Magrelli V , et al. Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions[J]. Technovation, 2023, 122: 102623.

DOI

35
蔡自兴, 蔡昱峰. 人工智能的大势、核心与机遇[J]. 冶金自动化, 2018, 42(2): 1- 5.

36
蔡自兴. 人工智能助推新基建数字化转型[N]. 光明日报, 2020-04-02(16).

37
西蒙. 人类的认知: 思维的信息加工理论[M]. 荆其诚, 张厚粲, 译. 北京: 科学出版社, 1986.

38
Shannon C E . A mathematical theory of communication[J]. The Bell System Thechnical Journal, 1948, 27(4): 623- 656.

DOI

39
Shannon C E . Programming a computer for playing chess[J]. Phylosophical Magazine, 1950, 41(4): 256- 275.

40
AI天才研究院. 人工智能与信息论: 从信息处理到知识表示[EB/OL]. (2023-12-27) [2025-03-18]. https://blog.csdn.net/universsky2015/arti-cle/details/137311775.

41
Cotterill R M J . Computer simula-tion in brain science[M]. Cambridge: Cambridge University Press, 1988.

42
Lu H M , Li Y J , Chen M , et al. Brain intelligence: Go beyond artificial intelligence[J]. Mobile Networks and Applications, 2018, 23(2): 368- 375.

DOI

43
McCulloch W S , Pitts W . A logical Calculus of the ideas immanent in nervous activity[J]. The Bulletin of Mathematical Biophysics, 1943, 5(4): 115- 133.

DOI

44
Rosenblatt F . The perceptron: A probabilistic model for information storage and organization in the brain[J]. Psychological Review, 1958, 65(6): 386- 408.

DOI

45
White B W , Rosenblatt F . Principles of neurodynamics: Perceptrons and the theory of brain mechanisms[J]. The American Journal of Psychology, 1963, 76(4): 705.

DOI

46
Hopfield J J . Neurons with graded response have collective computational properties like those of two-state neurons[J]. Proceedings of the National Academy of Sciences of the United States of America, 1984, 81(10): 3088- 3092.

47
LeCun Y , Bengio Y , Hinton G . Deep learning[J]. Nature, 2015, 521(7553): 436- 444.

DOI

48
Hopfield J J . Neural networks and physical systems with emergent collective computational abilities[M]. Ann Arbor: University of Michigan Press, 1975.

49
两位人工智能先驱获2024年诺贝尔物理学奖[EB/OL]. (2024-10-08) [2025-03-18]. https://baijiahao.bai-du.com/s?id=1812338883244432533&wfr=spider&for=pc.

50
人工智能两夺桂冠, 诺奖进入"AI时代"?[EB/OL]. (2024-10-12) [2025-03-18]. https://baijiahao.bai-du.com/s?id=1812688851073460277&wfr=spider&for=pc.

51
Kohonen T . Self-organized formation of topologically correct feature maps[J]. Biological Cybernetics, 1982, 43(1): 59- 69.

DOI

52
Wiener N . Cybernetics or Control and communication in the animal and the machine[M]. Cambridge, MA: MIT Press, 1948.

53
钱学森, 宋健. 工程控制论(修订版)[M]. 北京: 科学出版社, 1980.

54
Brooks R A , Stein L A . Building brains for bodies[J]. Autonomous Robots, 1994, 1(1): 7- 25.

DOI

55
蔡自兴, 刘丽珏, 蔡竞峰, 等. 人工智能及其应用[M]. 6版 北京: 清华大学出版社, 2020.

56
清华AI研究院院长张钹: 机器毫无自知之明, 知识对智能系统很重要[EB/OL]. (2019-07-30) [2025-03-18]. https://zhuanlan.zhihu.com/p/76198924?utm_id=0.

57
周志华: "数据、算法、算力"人工智能三要素, 在未来要加上"知识" [EB/OL]. (2020-08-08) [2025-03-18]. https://baijiahao.baidu.com/s?id=1674455605740066541&wfr=spider&for=pc.

58
Lieto A , Lebiere C , Oltramari A . The knowledge level in cognitive archi- tectures: Current limitations and possible developments[J]. Cognitive Systems Research, 2018, 48: 39- 55.

DOI

59
Tenorth M , Beetz M . Representations for robot knowledge in the KnowRob framework[J]. Artificial Intelligence, 2017, 247: 151- 169.

DOI

60
Vassev E, Hinchey M. Toward artificial intelligence through knowledge representation for awareness, soft-ware technology: 10 years of innovation[M]//IEEE Computer. Hoboken: John Wiley & Sons, 2018.

61
Leondes C T . Expert systems: The technology of knowledge management and decision making for the 21st century[M]. San Diego: Academic Press, 2002.

62
Bonatti P , Decker S , Polleres A , et al. Knowledge graphs: New directions for knowledge representation on the semantic web[J]. Dagstuhl Reports, 2019, 8: 29- 111.

63
Davis R , Shrobe H , Szolovits P . What is a knowledge representation?[J]. AI Magazine, 1993, 14(1): 17- 33.

64
Dechter R . Reasoning with probabilistic and deterministic graphical models: Exact algorithms, second edition, synthesis lectures on artificial intelligence and machine learning[M]. Cham: Morgan & Claypool Publishers, 2019.

65
Bezdek J C . On the relationship between neural networks, pattern recognition and intelligence[J]. Inter-national Journal of Approximate Reasoning, 1992, 6(2): 85- 107.

DOI

66
Bezdek J C. What is computational intelligence?[M]//Computational Intelligence Imitating Life. New York: IEEE Press, 1994.

67
Engelbrecht A P . Computational intelligence, an introduction[M]. New York: John Wiley & Sons, 2002.

68
Hannun A, Case C, Casper J, et al. Deep Speech: Scaling up end-to- end speech recognition[EB/OL]. [2025-03-18]. https://arxiv.org/abs/1412.5567v2.

69
Haykin S , Ye S . Principles of neural networks[M]. Beijing: Mechanical Industry Press, 2004.

70
Hecht N R . Neurocomputing[M]. Reading, MA: Addison-Wesley, 1990.

71
Waltz M , Fu K . A heuristic approach to reinforcement learning control systems[J]. IEEE Transactions on Automatic Control, 1965, 10(4): 390- 398.

DOI

72
Hinton G E . Deep belief networks[J]. Scholarpedia, 2009, 4(5): 5947.

DOI

73
Iqbal R , Doctor F , More B , et al. Big data analytics: Computational intelligence techniques and application areas[J]. Technological Forecasting and Social Change, 2018, 153: 119253.

74
Duan Y Q , Edwards J S , Dwivedi Y K . Artificial intelligence for deci-sion making in the era of Big Data-evolution, challenges and research agenda[J]. International Journal of Information Management, 2019, 48: 63- 71.

DOI

75
Duygu İ , Günay S . Design and implementation of the fuzzy expert system in Monte Carlo methods for fuzzy linear regression[J]. Applied Soft Computing, 2019, 77: 399- 411.

DOI

76
Thayyib P V , Mamilla R , Khan M , et al. State-of-the-art of artificial intelligence and big data analytics reviews in five different domains: A bibliometric summary[J]. Sustain-ability, 2023, 15(5): 4026.

77
Simon H A . Human cognition: Information processing theory of thinking[M]. Beijing: Science Press, 1986.

78
Fang S H , Tsao Y , Hsiao M J , et al. Detection of pathological voice using cepstrum vectors: A deep learning approach[J]. Journal of Voice, 2019, 33(5): 634- 641.

DOI

79
Michalewicz Z . Genetic Algo-rithms+Data Structures = Evolution Programs[M]. Berlin, Heidelberg: Springer-Verlag, 1994.

80
Szeliski R . Computer vision: Algo-rithms and applications[M]. London: Springer-Verlag, 2011.

81
Wang D S , Tan D P , Liu L . Particle swarm optimization algorithm: An overview[J]. Soft Computing, 2018, 22(2): 387- 408.

DOI

82
Xu R , Wunsch D . Survey of clustering algorithms[J]. IEEE Transactions on Neural Networks, 2005, 16(3): 645- 678.

DOI

83
郑金华, 蔡自兴. 自动区域划分的分区域搜索狭义遗传算法[J]. 计算机研究与发展, 2000, 37(4): 397- 400.

84
Rumelhart D E , Hinton G E , Williams R J . Learning representations by back-propagating errors[J]. Nature, 1986, 323(6088): 533- 536.

DOI

85
Turchenko V, Chalmers E, Luczak A. A deep convolutional auto- encoder with pooling-unpooling layers in caffe[EB/OL]. [2025-03-19]. https://arxiv.org/abs/1701.04949v1.

86
Cai Z X , Wang Y . A multiobjective optimization-basedevolutionaryalgo-rithm for constrained optimization[J]. IEEE Transactions on Evolutionary Computation, 2006, 10(6): 658- 675.

DOI

87
Wang Y , Xiang J , Cai Z X . A regularity model-based multiobjective estimation of distribution algorithm with reducing redundant cluster operator[J]. Applied Soft Computing, 2012, 12(11): 3526- 3538.

DOI

88
Cao D S , Xu Q S , Hu Q N , et al. ChemoPy: Freely available Python package for computational biology and chemoinformatics[J]. Bioinformatics, 2013, 29(8): 1092- 1094.

DOI

89
Mok E , Wong K , Shea G , et al. Design and algorithm development of an expert system for continuous health monitoring of sewer and storm water pipes[J]. Office Automation, 2014(Suppl1): 35- 38.

90
Salah K , Rehman M H U , Nizamud-din N , et al. Blockchain for AI: Review and open research challenges[J]. IEEE Access, 2019, 7: 10127- 10149.

DOI

91
Dai Y Y , Xu D , Maharjan S , et al. Blockchain and deep reinforcement learning empowered intelligent 5G beyond[J]. IEEE Network, 2019, 33(3): 10- 17.

DOI

92
Ren J K , Yu G D , He Y H , et al. Collaborative cloud and edge computing for latency minimization[J]. IEEE Transactions on Vehicular Technology, 2019, 68(5): 5031- 5044.

DOI

93
Wang X F , Ren X X , Qiu C , et al. Net-in-AI: A computing-power net-working framework with adaptability, flexibility, and profitability for ubiquitous AI[J]. IEEE Network, 35(1): 280- 288.

DOI

94
Xie R C , Li Z S , Wu J , et al. Energy-efficient joint caching and transcoding for HTTP adaptive streaming in 5G networks with mobile edge computing[J]. China Communications, 2019, 16(7): 229- 244.

DOI

95
狄筝, 曹一凡, 仇超, 等. 新型算力网络架构及其应用案例分析[J]. 计算机应用, 2022, 42(6): 1656- 1661.

96
贾庆民, 丁瑞, 刘辉, 等. 算力网络研究进展综述[J]. 网络与信息安全学报, 2021, 7(5): 1- 12.

97
Mitchell T M . Machine learning[M]. New York: McGraw-Hill, 1997.

98
Ryan D . Expert systems: Design, applications and technology[M]. New York: Nova Science Publishers, Inc., 2017.

99
Xiao X M, Cai Z X. Quantification of uncertainty and training of fuzzy logic systems[C]//Proceedings of IEEE International Conference on Intelligent Processing Systems. Piscataway NJ: IEEE, 1997: 321-326.

100
Lawrence S , Giles C L , Tsoi A C , et al. Face recognition: A convolutional neural-network approach[J]. IEEE Transactions on Neural Networks, 1997, 8(1): 98- 113.

DOI

101
LeCun Y, Bengio Y. Convolutional networks for images, speech, and time series. The handbook of brain theory and neural networks [M]//The handbook of brain theory and neural networks. Cambridge: MIT Press, 1998.

102
Simon D . Biogeography-based optimization[J]. IEEE Transactions on Evolutionary Computation, 2008, 12(6): 702- 713.

DOI

103
Michalewicz Z , Schoenauer M . Evolutionary algorithms for constrained parameter optimization problems[J]. Evolutionary Computation, 1996, 4(1): 1- 32.

DOI

104
Brenden M L , Ruslan S , Joshua B T . Human-level concept learning through probabilistic program induction[J]. Science, 2015, 350(6266): 1332- 1338.

DOI

105
Kang H , Yoo S J , Han D . Sentilexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews[J]. Expert Systems with Applications, 2012, 39(5): 6000- 6010.

DOI

106
蔡自兴, 郑金华. 面向agent的并行GA[J]. 湘潭矿业学院学报, 2002, 17(3): 41- 44.

DOI

107
Liu J H , Yang J G , Liu H P , et al. An improved ant colony algorithm for robot path planning[J]. Soft Computing, 2017, 21(19): 5829- 5839.

DOI

108
Wang Y , Liu H , Cai Z X , et al. An orthogonal design based constrained evolutionary optimization algorithm[J]. Engineering Optimization, 2007, 39(6): 715- 736.

DOI

109
许大文. 什么是大模型[EB/OL]. (2023-12-14)[2025-03-18]. https://www.meipian.cn/4z3dxff8.

110
DeepSeek[EB/OL]. (2025-04-05) [2025-04-05]. https://baike.baidu.com/item/DeepSeek/65258669.

111
ChatGPT[EB/OL]. [2025-03-18]. https://baike.so.com/doc/30347871-31986167.htm.

112

113
Ren X X , Qiu C , Wang X F , et al. AI-bazaar: A cloud-edge computing power trading framework for ubiquitous AI services[J]. IEEE Transactions on Cloud Computing, 2022, 11(3): 2337- 2348.

114
Xie R C , Tang Q Q , Qiao S , et al. When serverless computing meets edge computing: Architecture, challenges, and open issues[J]. IEEE Wireless Communications, 2021, 28(5): 126- 133.

DOI

115
雷波, 刘增义, 王旭亮, 等. 基于云、网、边融合的边缘计算新方案: 算力网络[J]. 电信科学, 2019, 35(9): 44- 51.

116
郑纬民. 新基建中的高性能人工智能算力基础设施的架构与测评[J]. 机器人产业, 2020(6): 51- 56.

DOI

117
蔡自兴. 人工智能产业化的历史、现状与发展趋势[J]. 冶金自动化, 2019, 43(2): 1- 5.

118
蔡自兴. 人工智能对人类的深远影响[J]. 高技术通讯, 1995, 5(6): 55- 57.

DOI

119
Jason F, and Seamans R. AI and the Economy[M]//Innovation Policy and the Economy volume 20. Chicago: University of Chicago Press, 2018.

120
蔡自兴. 中国人工智能40年[J]. 科技导报, 2016, 34(15): 12- 32.

121
Fan H . Research on innovation and application of 5G using artificial intelligence-based image and speech recognition technologies[J]. Journal of King Saud University-Science, 2023, 35(4): 102626.

DOI

122
Zhu W B , Gui R Z , Guo R . Unveiling the nexus and promoting integration of diverse factors: Prospects of big data-driven artificial intelligence technology in achieving carbon neutrality in Chongming District[J]. Water-Energy Nexus, 2023, 6: 112- 121.

DOI

123
Pelusi D , Mascella R , Tallini L , et al. Neural network and fuzzy system for the tuning of Gravitational Search Algorithm parameters[J]. Expert Systems with Applications, 2018, 102: 234- 244.

DOI

124
Waschull S , Emmanouilidis C . Assessing human-centricity in AI enabled manufacturing systems: A socio-technical evaluation methodology[J]. IFAC-PapersOnLine, 2023, 56(2): 1791- 1796.

DOI

125
蔡自兴. 人工智能的社会问题[J]. 团结, 2017(6): 20- 27.

DOI

126
蔡自兴. 展望人工智能发展的若干问题[J]. 高技术通讯, 1995, 5(7): 59- 61.

DOI

文章导航

/