A Brief Introduction to the Use of Machine Learning Techniques in the Analysis of Agent-Based Models

8 Pages Posted: 14 Nov 2015

See all articles by María Pereda

María Pereda

Universidad Politécnica de Madrid

José Santos

University of Burgos

Jose Manuel Galan

Universidad de Burgos

Date Written: November 12, 2015

Abstract

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.

Keywords: Agent based modeling, Agent based simulation, Complex Systems, Simulation of socio-economic systems, Decision making support tolos, machine learning, statistical learning

JEL Classification: C14

Suggested Citation

Pereda, María and Santos, José and Galan, Jose Manuel, A Brief Introduction to the Use of Machine Learning Techniques in the Analysis of Agent-Based Models (November 12, 2015). Available at SSRN: https://ssrn.com/abstract=2689676 or http://dx.doi.org/10.2139/ssrn.2689676

María Pereda (Contact Author)

Universidad Politécnica de Madrid ( email )

Ciudad Universitaria
Madrid, MA Madrid 28040
Spain

José Santos

University of Burgos ( email )

Hospital del Rey, s/n
Burgos, 09001
Spain

Jose Manuel Galan

Universidad de Burgos ( email )

Burgos
Spain

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