#Netlogo round install#
#Netlogo round software#
#Netlogo round free#

With the NetLogo-Mathematica link, you can run all of these tools side-by-side with NetLogo’ ( Bakshy & Wilensky 2007), RNetLogo’s scope is virtually the same: all these tools support systematic and comprehensive analyses of model behaviour. Such a seamless integration was already the reason for linking Mathematica ( Wolfram Research 2010) and NetLogo ( Bakshy & Wilensky 2007), which was designed to make use of the Mathematica tools for ‘advanced import capabilities, statistical functions, data visualization and document creation. However, a seamless integration of both tools would facilitate the combined use of R and NetLogo. R is already widely used to analyse file output of simulation models, including those implemented in NetLogo. RNetLogo is not designed for using R within NetLogo programs but for running and exploring simulation experiments of a given NetLogo program.

#Netlogo round install#

to call NetLogo programs and commands from R: the R user community is much larger than the NetLogo user community so it makes sense to provide a tool that starts with R the R extension can, for technical reasons, be cumbersome to install whereas RNetLogo is as easy to load as any other R package RNetLogo can be used to create self-documented simulation experiments and reports using Sweave ( Leisch 2002), SWord ( Baier 2009) or odfWeave ( Kuhn 2010) RNetLogo opens a way to integrate NetLogo simulation into spreadsheets using RExel ( Heidberger & Neuwirth 2009), ROOo ( Drexel 2011) or R4Calc ( Gryc 2008). There are, however, good reasons for linking R and NetLogo also the other way round, i.e. Or, if random numbers are needed from probability distributions which are not provided by NetLogo, they can easily be imported from R. For example, if a population model of a territorial animal requires, while the model is running, to calculate home range sizes based on the animals’ movement, existing R packages for calculating home range sizes can be used (e.g., Calenge 2006).

It is mainly designed for using R commands to support the implementation of IBMs, or their sub models.

It allows calling any R command from a NetLogo program. One such link already exists: the R extension of NetLogo ( Thiele & Grimm 2010). Linking NetLogo with R is therefore desirable.

#Netlogo round software#

Both R and NetLogo are increasingly used in their fields, slowly but surely turning into standard software platforms which are also the basis for training the next generation of researchers (see, e.g., Bolker 2008 Railsback & Grimm 2011).

#Netlogo round free#

It is a package for the free statistics software R ( R Development Core Team 2011) which allows running and analysing IBMs that are implemented in NetLogo ( Wilensky 1999), a free software platform for implementing individual-based or agent-based models. 2009), storing simulation results in a systematic way and using statistical toolboxes for analysing these results. Much more could be learned from IBMs if they would be embedded in a rigorous framework for designing simulation experiments ( Oh et al. A remaining challenge, however, is that analyses of many IBMs are still more or less superficial ( Grimm 1999 Grimm & Railsback 2005 Lorscheid, Heine & Meyer 2011).

IBMs are an established and widely used tool in ecology and evolution ( DeAngelis & Mooij 2005). Individual-based models (IBMs) are simulation models that explicitly represent individual organisms and how they interact with each other and their environment ( Grimm & Railsback 2005 Thiele, Kurth & Grimm 2011).