经济复杂性系统主体学习算法理论综述

被引:3
作者
鲜于波
梅琳
机构
[1] 广东省中山大学岭南学院
关键词
学习算法; 经济复杂系统; 计算智能; 实验经济学;
D O I
10.13306/j.1672-3813.2007.02.009
中图分类号
F224 [经济数学方法];
学科分类号
0701 ; 070104 ;
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。
引用
收藏
页码:77 / 92
页数:16
相关论文
共 8 条
[1]  
行为博弈[M]. 中国人民大学出版社 , (美)科林·凯莫勒(ColinF.Camerer)著, 2006
[2]   The behavior of the exchange rate in the genetic algorithm with agents having long memory [J].
Xu, Yiping .
JOURNAL OF EVOLUTIONARY ECONOMICS, 2006, 16 (03) :279-297
[3]   Modeling Exchange Rate Behavior with a Genetic Algorithm [J].
C. Lawrenz ;
F. Westerhoff .
Computational Economics, 2003, 21 (3) :209-229
[4]  
Exchange-Rates Forecasting: A Hybrid Algorithm Based on Genetically Optimized Adaptive Neural Networks[J] . Andreas S. Andreou,Efstratios F. Georgopoulos,Spiridon D. Likothanassis.Computational Economics . 2002 (3)
[5]   Learning and behavioral stability - An economic interpretation of genetic algorithms [J].
Riechmann, T .
JOURNAL OF EVOLUTIONARY ECONOMICS, 1999, 9 (02) :225-242
[6]   Using co-evolutionary programming to simulate strategic behaviour in markets [J].
Price, TC .
JOURNAL OF EVOLUTIONARY ECONOMICS, 1997, 7 (03) :219-254
[7]  
Bounded rationality, neural network and folk theorem in repeated games with discounting[J] . In-Koo Cho.Economic Theory . 1994 (6)
[8]  
On designing economic agents that behave like human agents[J] . W. Brian Arthur.Journal of Evolutionary Economics . 1993 (1)