Evolving Agent-based Models Using Complexification Approach

被引:0
|
作者
Wagner, Michael [1 ]
Cai, Wentong [2 ]
Lees, Michael H. [3 ]
Aydt, Heiko [1 ]
机构
[1] TUM CREATE, 1 Create Way, Singapore 138602, Singapore
[2] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore
[3] Univ Amsterdam, Inst Informat, Amsterdam, Netherlands
基金
新加坡国家研究基金会;
关键词
Evolutionary Computing; Agent-based Simulation; Modelling; Artificial Life;
D O I
10.1016/j.procs.2014.05.028
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper focuses on parameter search for multi-agent based models using evolutionary algorithms. Large numbers and variable dimensions of parameters require a search method which can efficiently handle a high dimensional search space. We are proposing the use of complexification as it emulates the natural way of evolution by starting with a small constrained search space and expanding it as the evolution progresses. We examined the effects of this method on an EA by evolving parameters for two multi-agent based models.
引用
收藏
页码:310 / 321
页数:12
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