EvoPER -- An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology, Agents and Multi-Agent Systems, Scientific Computing and Simulation
- Keywords
- Individual-Based Modeling, Parameter Estimation, Evolutionary Computation, Systems Biology}, Systems Biology
- Copyright
- © 2016 Prestes García et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. EvoPER -- An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast. PeerJ Preprints 4:e2279v1 https://doi.org/10.7287/peerj.preprints.2279v1
Abstract
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 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 Repast models.
Author Comment
This is a preprint submission to PeerJ Preprints.