人工智能心理学研究的知识图谱分析

借助CitespaceⅢ对选自WoS的人工智能心理学研究文献进行知识图谱探析,结合自动聚类视图与议题标签展现了人工智能心理学领域的6个知识聚类:#0人工智能解决问题议题;#1人工与人类认知共性议题;#2人工智能学习议题;#3人工智能脑科学议题;#4人工智能环境认知议题;#5人工智能表征议题。在深入探究各聚类的核心与热点知识的基础上分析了人工智能心理学发展的各阶段特征:1.上世纪50年代图灵和米勒等人对机器认知与学习等概念的猜想与初探;2.70-90年代纽厄尔、西蒙和莱尔德等人基于模块记忆与层级分析对人工智能信息处理模型的系统性构建;3.本世纪初基于神经生理学的降维数据认知理论的发展;4.当下人工智能贝叶斯大脑与深度学习理论的兴起。

An Analysis and Visualization of Artificial Intelligence Psychology Using Knowledge Map

The knowledge map of AI psychology articles selected from WoS are analyzed by means of Citespace Ⅲ.Six clusters of AI ethics knowledge are showed in reference to the automatic clustering view and topic tags,which respectively are,#0 AI problems solving research,#1 artificial and human cognitive commonness,#2 AI learning research,#3 AI brain cognition research,#4 AI environmental cognition research,and #5 AI representation research.Based on the analysis of the representative cited references and hot spot knowledge,4 stages of AI psychology research in nearly a century are summarized:1.in the 1950s,the conjecture and preliminary exploration of concepts about machine cognition and learning proposed by Turing and Miller et al;2.in the 1960s-1990s,the information processing models of AI based on chunking memory and hierarchy analysis systematically constructed by Newell,Herbert,and Laird et al;3.at the beginning of the 21st century,the development of the cognition theory of dimension reduction data based on the Neurophysiology;4.at present,the rise of Bayesian brain and deep learning theory of AI.