A Brief Introduction to the Use of Machine Learning Techniques in the Analysis of Agent-Based Models
A Brief Introduction to the Use of Machine Learning Techniques in the Analysis of Agent-Based Models
复制标题
机器学习技术在基于代理的模型分析中的使用简介
DOI：
--
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
José Manuel Galán
中科院分区：
文献类型：
--
作者：
M. Pereda;J. I. Santos;José Manuel Galán
本文简要介绍了从机器和统计学习领域引入的一些基本概念，这些概念对于分析复杂的基于代理的模型（ABM）很有用。本文提出了一些实验设计的指导原则。然后，它侧重于考虑反弹道导弹模拟作为一个计算实验相关的参数与感兴趣的响应变量，即从模拟中获得的统计。这种观点提供了使用监督学习算法来拟合具有参数的响应的机会。拟合模型可以用来更好地解释和理解反弹道导弹的参数和模拟结果之间的关系。
This paper gives a succinct introduction to some basic concepts imported from the fields of Machine and Statistical Learning that can be useful in the analysis of complex agent-based models (ABM). The paper presents some guidelines in the design of experiments. It then focuses on considering an ABM simulation as a computational experiment relating parameters with a response variable of interest, i.e. a statistic obtained from the simulation. This perspective gives the opportunity of using a supervised learning algorithm to fit the response with the parameters. The fitted model can be used to better interpret and understand the relation between the parameters of the ABM and the results in the simulation.