Paper Info
Title
EvoPER - An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast.
Abstract
Individual-based models are complex and they normally have an elevated number of input parameterswhich 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 enoughinformation 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 thedeviations of simulated and observed data. In practice, most of the times, is computationally unfeasible totraverse 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 usingevolutionary 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-basedmodeling toolkit Repast.
Year
Venue
Field
2016
PeerJ PrePrints
Paleontology,Mathematical optimization,Computer science,Systems biology,Evolutionary computation,Algorithm,Implementation,Estimation theory,R package,Traverse
DocType
Volume
Citations 
Journal
4
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
A. García121.18
Alfonso Rodríguez-Patón243551.44