EvoPER-An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast

Prestes García, Antonio y Rodríguez-Patón Aradas, Alfonso (2016). EvoPER-An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast. "PeerJ Preprint", v. 1 (n. 2279); pp. 1-10. ISSN 2167-9843. https://doi.org/doi.org/10.7287/peerj.preprints.2279v1.

Descripción

Título: EvoPER-An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast
Autor/es:
  • Prestes García, Antonio
  • Rodríguez-Patón Aradas, Alfonso
Tipo de Documento: Artículo
Título de Revista/Publicación: PeerJ Preprint
Fecha: 2016
Volumen: 1
Materias:
Palabras Clave Informales: Individual-Based Modeling; Parameter Estimation; Evolutionary Computation; Systems Biology
Escuela: E.T.S. de Ingenieros Informáticos (UPM)
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Individual-based models are complex and they normally have an elevated number of input parameters which must be tuned in order to reproduce the experimental or observed data as accurately as possible. Hence one of the weakest points of such kind of models is the fact that rarely the modeler has the enough information about the correct values or even the acceptable range for the input parameters. Therefore, several parameter combinations must be checked to find an acceptable set of input factors minimizing the deviations of simulated and observed data. In practice, most of the times, is computationally unfeasible to traverse the complete search space to check all parameter combination in order to find the best of them. That is precisely the kind of combinatorial problem suitable for evolutionary computation techniques. In this work we present the EvoPER, an R package for simplifying the parameter estimation using evolutionary computation techniques. The current version of EvoPER includes implementations of PSO, SA and ACO algorithms for parameter estimation of models generated with the open source agent-based modeling toolkit Repast.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
FP7612146PLASWIRESUniversidad Politécnica de MadridEngineering multicellular biocircuits: programming cell-cell communication using plasmids as wires

Más información

ID de Registro: 45442
Identificador DC: http://oa.upm.es/45442/
Identificador OAI: oai:oa.upm.es:45442
Identificador DOI: doi.org/10.7287/peerj.preprints.2279v1
URL Oficial: https://peerj.com/preprints/2279/
Depositado por: Memoria Investigacion
Depositado el: 30 Oct 2017 17:19
Ultima Modificación: 30 Oct 2017 17:19
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