Lessons from a comprehensive validation of an agent based - model the experience of the Pampas Model of Argentinean agricultural systems

There are few published examples of comprehensively validated large-scale land-use agent-based models [ABMs]. We present guidelines for doing so, and provide an example in the context of the Pampas Model [PM], an ABM aimed to explore the dynamics of structural and land use changes in the agricultura...

Descripción completa

Detalles Bibliográficos
Otros Autores: Bert, Federico E., Rovere, Santiago L., Macal, Charles M., North, Michael J., Podestá, Guillermo P.
Formato: Artículo
Lenguaje:Español
Materias:
Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2014bert.pdf
LINK AL EDITOR
Aporte de:Registro referencial: Solicitar el recurso aquí
LEADER 07519cab a22012617a 4500
001 AR-BaUFA000635
003 AR-BaUFA
005 20220214114153.0
008 181208t2014 |||||o|||||00||||spa d
999 |c 47031  |d 47031 
022 |a 0304-3800 
024 |a 10.1016/j.ecolmodel.2013.11.024 
040 |a AR-BaUFA  |c AR-BaUFA 
245 1 0 |a Lessons from a comprehensive validation of an agent based - model   |b the experience of the Pampas Model of Argentinean agricultural systems 
520 |a There are few published examples of comprehensively validated large-scale land-use agent-based models [ABMs]. We present guidelines for doing so, and provide an example in the context of the Pampas Model [PM], an ABM aimed to explore the dynamics of structural and land use changes in the agricultural systems of the Argentine Pampas. Many complementary strategies are proposed for validation of ABM's. We adopted a validation framework that relies on two main streams: [a] validation of model processes and components during model development, which involved a literature survey, design based on similar models, involvement of stakeholders, and focused test scenarios and [b] empirical validation, which involved comparisons of model outputs from multiple realistic simulations against real world data. The design process ensured a realistic model ontology and representative behavioral rules. As result, we obtained reasonable outcomes from a set of initial and simplified scenarios: the PM successfully reproduced the direction of the primary observed structural and land tenure patterns, even before calibration. The empirical validation process lead to tuning and further development of the PM. After this, the PM was able to reproduce not only the direction but also the magnitude of the observed changes. The main lesson from our validation process is the need for multiple validation strategies, including empirical validation. Approaches intended to validate model processes and components may lead to structurally realistic models. However, some kind of subsequent empirical validation is needed to assess the model's ability to reproduce observed results. 
653 0 |a AGENT-BASED MODEL 
653 0 |a AGRICULTURAL SYSTEM 
653 0 |a AGRICULTURE 
653 0 |a ARGENTINA 
653 0 |a COMPARATIVE STUDY 
653 0 |a COMPUTATIONAL METHODS 
653 0 |a COMPUTER SIMULATION 
653 0 |a EMPIRICAL VALIDATION 
653 0 |a FARMING SYSTEM 
653 0 |a LAND TENURE 
653 0 |a LAND TENURE PATTERNS 
653 0 |a LAND USE 
653 0 |a NUMERICAL MODEL 
653 0 |a PAMPAS 
653 0 |a REALISTIC SIMULATION 
653 0 |a SIMULATION 
653 0 |a STAKEHOLDER 
653 0 |a VALIDATION 
653 0 |a VALIDATION STRATEGIES 
700 1 |a Bert, Federico E.  |9 12448 
700 1 |9 68359  |a Rovere, Santiago L. 
700 1 |a Macal, Charles M.  |9 70357 
700 1 |9 69867  |a North, Michael J. 
700 1 |a Podestá, Guillermo P.  |9 23487 
773 |t Ecological Modelling  |g vol. 273 (2014), p.284-298 
856 |u http://ri.agro.uba.ar/files/intranet/articulo/2014bert.pdf  |i En reservorio  |q application/pdf  |f 2014bert  |x MIGRADOS2018 
856 |u http://www.elsevier.com/  |x MIGRADOS2018  |z LINK AL EDITOR 
900 |a as 
900 |a 20150908 
900 |a N 
900 |a SCOPUS 
900 |a a 
900 |a s 
900 |a ARTICULO 
900 |a EN LINEA 
900 |a 03043800 
900 |a 10.1016/j.ecolmodel.2013.11.024 
900 |a ^tLessons from a comprehensive validation of an agent based-model^sThe experience of the Pampas Model of Argentinean agricultural systems 
900 |a ^aBert^bF.E. 
900 |a ^aRovere^bS.L. 
900 |a ^aMacal^bC.M. 
900 |a ^aNorth^bM.J. 
900 |a ^aPodestá^bG.P. 
900 |a ^aBert^bF. E. 
900 |a ^aRovere^bS. L. 
900 |a ^aMacal^bC. M. 
900 |a ^aNorth^bM. J. 
900 |a ^aPodestá^bG. P. 
900 |a Bert, F.E. Facultad de Agronomía, Universidad de Buenos Aires - CONICET, Av. San Martín 4453, Buenos Aires, Argentina 
900 |a Rovere, S.L. Facultad de Ingeniería, Universidad de Buenos Aires, Av. Las Heras 2214, Buenos Aires, Argentina 
900 |a Macal, C.M. Argonne National Laboratory, 9700 S Cass Avenue, Argonne, IL 60439, United States 
900 |a North, M.J. Argonne National Laboratory, 9700 S Cass Avenue, Argonne, IL 60439, United States 
900 |a Podestá, G.P. Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149, United States 
900 |a ^tEcological Modelling^cEcol. Model. 
900 |a eng 
900 |a 284 
900 |a ^i 
900 |a Vol. 273 
900 |a 298 
900 |a AGENT-BASED MODEL 
900 |a AGRICULTURAL SYSTEM 
900 |a AGRICULTURE 
900 |a ARGENTINA 
900 |a COMPARATIVE STUDY 
900 |a COMPUTATIONAL METHODS 
900 |a COMPUTER SIMULATION 
900 |a EMPIRICAL VALIDATION 
900 |a FARMING SYSTEM 
900 |a LAND TENURE 
900 |a LAND TENURE PATTERNS 
900 |a LAND USE 
900 |a NUMERICAL MODEL 
900 |a PAMPAS 
900 |a REALISTIC SIMULATION 
900 |a SIMULATION 
900 |a STAKEHOLDER 
900 |a VALIDATION 
900 |a VALIDATION STRATEGIES 
900 |a There are few published examples of comprehensively validated large-scale land-use agent-based models [ABMs]. We present guidelines for doing so, and provide an example in the context of the Pampas Model [PM], an ABM aimed to explore the dynamics of structural and land use changes in the agricultural systems of the Argentine Pampas. Many complementary strategies are proposed for validation of ABM's. We adopted a validation framework that relies on two main streams: [a] validation of model processes and components during model development, which involved a literature survey, design based on similar models, involvement of stakeholders, and focused test scenarios and [b] empirical validation, which involved comparisons of model outputs from multiple realistic simulations against real world data. The design process ensured a realistic model ontology and representative behavioral rules. As result, we obtained reasonable outcomes from a set of initial and simplified scenarios: the PM successfully reproduced the direction of the primary observed structural and land tenure patterns, even before calibration. The empirical validation process lead to tuning and further development of the PM. After this, the PM was able to reproduce not only the direction but also the magnitude of the observed changes. The main lesson from our validation process is the need for multiple validation strategies, including empirical validation. Approaches intended to validate model processes and components may lead to structurally realistic models. However, some kind of subsequent empirical validation is needed to assess the model's ability to reproduce observed results. 
900 |a 273 
900 |a 2014 
900 |a ^cH 
900 |a AAG 
900 |a AGROVOC 
900 |a 2014bert 
900 |a AAG 
900 |a http://ri.agro.uba.ar/files/intranet/articulo/2014bert.pdf 
900 |a http://www.elsevier.com/ 
900 |a http://www.scopus.com/inward/record.url?eid=2-s2.0-84890349350&partnerID=40&md5=85a182ee0f783affb30590784a71e6c2 
900 |a ^a^b^c^d^e^f^g^h^i 
900 |a OS 
942 0 0 |c ARTICULO  |2 udc 
942 0 0 |c ENLINEA  |2 udc