NetLogoR
Build and Run Spatially Explicit Agent-Based Models
Build and run spatially explicit agent-based models using only the R platform. 'NetLogoR' follows the same framework as the 'NetLogo' software (Wilensky (1999) http://ccl.northwestern.edu/netlogo/) and is a translation in R of the structure and functions of 'NetLogo'. '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' framework, coupled with the versatility, power and massive resources of the R software. Examples of two models from the NetLogo software repository (Ants http://ccl.northwestern.edu/netlogo/models/Ants) and Wolf-Sheep-Predation (http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation), and a third, Butterfly, from Railsback and Grimm (2012) https://www.railsback-grimm-abm-book.com/, all 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 (https://ccl.northwestern.edu/netlogo/docs/programming.html) and a dictionary of 'NetLogo' primitives (https://ccl.northwestern.edu/netlogo/docs/dictionary.html) equivalences are also available. NOTE: To increment 'time', these functions can use a for loop or can be integrated with a discrete event simulator, such as 'SpaDES' (https://cran.r-project.org/package=SpaDES). The suggested package 'fastshp' can be installed with 'install.packages("fastshp", repos = ("https://rforge.net"), type = "source")'.
- Version1.0.5
- R version≥ 4.1
- LicenseGPL-3
- Needs compilation?No
- Languageen-CA
- NetLogoR citation info
- Last release01/08/2024
Documentation
Team
Eliot J B McIntire
Alex M Chubaty
Show author detailsRolesAuthorSarah Bauduin
His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources Canada
Show author detailsRolesCopyright holder
Insights
Last 30 days
This package has been downloaded 411 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 13 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 4,798 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was May 02, 2024 with 175 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports3 packages
- Suggests12 packages