RT info:eu-repo/semantics/article
T1 Asking the Oracle: introducing forecasting principles into agent-based modelling
A1 Hassan, Samer
A1 Arroyo, Javier
A1 Galán Ordax, José Manuel
A1 Antunes, Luis
A1 Pavón Mestras, Juan
K1 Forecasting
K1 Guidelines
K1 Prediction
K1 Agent-Based modelling
K1 Modelling process
K1 Social simulation
K1 Industrial management
K1 Gestión de empresas
AB This paper presents a set of guidelines, imported from the field of forecasting, that can help social simulation and, more specifically, agent-based modelling practitioners to improve the predictive performance and the robustness of their models. The presentation starts with a discussion on the current debate on prediction in social processes, followed by an overview of the recent experience and lessons learnt from the field of forecasting. This is the basis to define standard practices when developing agent-based models under the perspective of forecasting experimentation. In this context, the guidelines are structured in six categories that correspond to key issues that should be taken into account when building a predictor agent-based model: the modelling process, the data adequacy, the space of solutions, the expert involvement, the validation, and the dissemination and replication. The application of these guidelines is illustrated with an existing agent-based model. We conclude by tackling some intrinsic difficulties that agent-based modelling often faces when dealing with prediction models.
PB SimSoc Consortium
SN 1460-7425
YR 2013
FD 2013-06
LK http://hdl.handle.net/10259/3926
UL http://hdl.handle.net/10259/3926
LA eng
NO project Social Ambient Assisting Living - Methods (SociAAL), supported by Spanish Council for Science and Innovation, with grant TIN2011-28335-C02-01 and the Spanish MICINN project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010). We also thank the support from the Programa de Creación y Consolidación de Grupos de Investigación UCM-BSCH, GR35/10-A (921354)
DS Repositorio Institucional de la Universidad de Burgos
RD 04-dic-2024