智能科学与技术学报 ›› 2023, Vol. 5 ›› Issue (2): 133-142.doi: 10.11959/j.issn.2096-6652.202314

• 评论智能 •    下一篇

McCulloch-Pitts人工神经元模型80周年纪念:思想、方法与意义

缪青海1, 王雨桐2, 吕宜生1,2, 那晓翔3, 王飞跃1,2   

  1. 1 中国科学院大学人工智能学院,北京 100049
    2 中国科学院自动化研究所复杂系统管理与控制国家重点实验室,北京 100190
    3 剑桥大学工程系,英国 剑桥 CB2 1PZ
  • 修回日期:2023-06-10 出版日期:2023-06-15 发布日期:2023-06-10
  • 作者简介:缪青海(1979- ),男,中国科学院大学人工智能学院副教授,主要研究方向为智能系统、平行智能和机器学习
    王雨桐(1994- ),女,中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员,主要研究方向为计算机视觉、图像异常检测
    吕宜生(1983- ),男,中国科学院自动化研究所研究员,主要研究方向为人工智能、机器学习、深度学习、智能驾驶、智能交通和交通大数据
    那晓翔(1984- ),男,英国剑桥大学工程系长聘助理教授,博士生导师。主要研究方向为驾驶员—车辆闭环系统动力学、智能车载信息系统的设计与开发、重型商用车节能减排特性的分析与评价
    王飞跃(1961- ),男,中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任,主要研究方向为平行系统的方法与应用、社会计算、平行智能和知识自动化
  • 基金资助:
    国家自然科学基金项目(62271485);国家自然科学基金项目(61903363);国家自然科学基金项目(U1811463)

In celebration of McCulloch-Pitts ANN model’s 80th anniversary: its origin, principle, and influence

Qinghai MIAO1, Yutong WANG2, Yisheng LV1,2, Xiaoxiang NA3, Fei-Yue WANG1,2   

  1. 1 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
    2 State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    3 Cambridge University, Cambridge CB2 1PZ, UK
  • Revised:2023-06-10 Online:2023-06-15 Published:2023-06-10
  • Supported by:
    The National Natural Science Foundation of China(62271485);The National Natural Science Foundation of China(61903363);The National Natural Science Foundation of China(U1811463)

摘要:

1943年,Warren McCulloch和Walter Pitts发表论文《神经活动内在思想的逻辑演算》,证明可以使用逻辑演算描述神经网络的运行机理,拓展了计算神经科学的领域前沿,奠定了人工神经网络的发展基础。恰逢M-P论文发表80周年之际,结合时代背景和作者学术生涯的变迁,探索M-P理论的思想源泉;借助原文中的示例,概述M-P模型的基本原理;以作者对循环因果和反馈机制的研究为主线,探讨M-P模型对信息科学发展的影响、对控制论发展的贡献,及其在当今人工智能大模型时代的意义。

关键词: M-P模型, 人工神经网络, 循环因果, 控制论, 平行系统, 人工智能

Abstract:

In 1943, Warren McCulloch and Walter Pitts published a paper titled “A logical calculus of the ideas immanent in nervous activity”, which demonstrated that the functioning of neural networks could be described using logical calculus.This expanded the field of computational neuroscience and laid the foundation for the development of artificial neural networks.On the occasion of the 80th anniversary of the publication of the M-P paper, the intellectual origins of the M-P theory was explored, taking into account the historical context and the authors’ career trajectories.With the help of examples from the original paper, the basic principles of the M-P model were outlined, and its advantages and limitations were summarized.Furthermore, the impact of the M-P theory on the development of information science was discussed, focusing on the authors’ contributions to cybernetics, including their work on circular causality and feedback mechanisms, which provided a foundation for the development of modern artificial intelligence technologies such as parallel intelligence and large-scale models.

Key words: M-P model, neural network, circular causality, cybernetics, parallel system, artificial intelligence

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