摘要
对经济复杂性系统研究文献中常见的主体学习算法进行了一个全面的梳理。将学习算法分为来自智能计算或演化计算的学习算法以及来自心理学和实验经济学的学习算法,并结合文献介绍了各类学习模型在经济学研究中的主要应用。还回顾了文献中对各种算法的分析比较,并对学习算法的发展前景进行了展望。由于学习算法还是一个相对较新的领域,对经济系统中个体学习行为需要进行更加深入的研究和探索。
This paper gives a comprehensive overview about agent learning algorithms used in economic complexity system research. This paper divides the evolutionary algorithms into two kinds： one comes from artificial intelligent and another comes from psychology and experiment economics. The paper then analyses the application of learning model in economics theory. This paper also reviews the comparison of these learning models made in literature and discusses its future development. Because agent learning model research is a relatively new field, so it calls for more research and development.
出处
《复杂系统与复杂性科学》
EI
CSCD
2007年第2期77-92,共16页
Complex Systems and Complexity Science
关键词
学习算法
经济复杂系统
计算智能
实验经济学
learning algorithms
economic complexity system
computational intelligence
experimental economics
