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

install.packages("NetLogoR")

From GitHub

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

Getting help

We have created a Google group for users to get help implementing their models using the package. Please see the discussions at https://groups.google.com/g/netlogor.