Build and Run Spatially Explicit Agent-Based Models.

NetLogoR

Build and run spatially explicit agent-based models in R

NetLogoR is an R package to build and run spatially explicit agent-based models using only the R platform (Bauduin et al., 2019). It follows the same framework as NetLogo (Wilensky, 1999) and is a translation in R language of the structure and functions of NetLogo (NetLogo primitives). NetLogoR provides new R classes to define model agents and functions to implement spatially explicit agent-based models in the R environment. This package allows benefiting of the fast and easy coding phase from the highly developed NetLogo's framework, coupled with the versatility, power and massive resources of the R software.

Getting Started

Examples of three models (Ants, Butterfly (Railsback and Grimm, 2012) and Wolf-Sheep-Predation) written using NetLogoR are available. The NetLogo code of the original version of these models is provided alongside. A programming guide inspired from the NetLogo Programming Guide and a dictionary of NetLogo primitives equivalences are also available. A model simulating the wolf life cycle written using NetLogoR has been published (Bauduin et al., 2020) with the (code available on GitHub).

Installing NetLogoR

From CRAN

Currently, the package is not on CRAN due to some dependencies that were removed from CRAN. It will be there soon.

In the mean time, please use:

# install.packages("NetLogoR")
install.packages("NetLogoR", repos = c(https://predictiveecology.r-universe.dev, getOption("repos")))

From GitHub

#install.packages("devtools")
devtools::install_github("PredictiveEcology/NetLogoR")

Getting help

Please email developers or start an issue on the NetLogoR web page.