Hello,

[Scratch Cat (Scratchy)]

Can you teach me NetLogo? I do not know how to use it.

[Wannes...@hotmail.be]

I suggest starting out the tutorials in the Netlogo users manual  NetLogo 6.2.2 User Manual (northwestern.edu).

Other sources that I personally used are:
-Agent-Based and Individual-Based Modeling by Railsback & Grimm (2019). This book is definitely a good start, not only for learning Netlogo but the ideas behind agent-based modelling in general.
-The online course "Introduction to Agent-Based Modeling (2021)" on Complexity Explorer is also a good one for getting used to what you can do with Netlogo

Op zaterdag 24 september 2022 om 19:49:35 UTC+2 schreef maaha...@gmail.com:

[Alan G. Isaac]

Basic background: https://subversion.american.edu/aisaac/notes/netlogoIntroduction.html
Wurzer's teaching videos: https://www.youtube.com/watch?v=XJ-gO-yAwHU

[Michael Tamillow]

First things first.

Fill out the form, Download, install, click to open the application. https://ccl.northwestern.edu/netlogo/download.shtml

Go to "File" -> "Models Library" find "Sample Models/Ants" the same model can be found online here: https://www.netlogoweb.org/launch#https://www.netlogoweb.org/assets/modelslib/Sample%20Models/Biology/Ants.nlogo

I like this model because it is super simple and interesting. Click "setup" and "go". Then slide around the values and click again. When you are comfortable with this, go to the information tab, and then code tab.

This is how I got my 4-year olds started. There are really 3 levels to learn, and they can be thought of in terms of the tabs, "interface", "info", and "code". I would say they go in that order.

1.) Interface - this is the observer, the experience of the experimentalist. We are all scientists at some level, testing and learning from the environment. Everyone, even a 4 year old, is a scientist at some level.

2.) Info - This is the domain of the complexity scientist, someone whose understanding is rooted in the principles of the current knowledge of what might best be called "solved science". This is where the ideation of what complexity is worth exploring happens. For example, we can model "orbits" using current velocity and the force of gravity. In this case two known forces create a new phenomenon. This is the beautiful consistency of science!

3.) Code - We are getting more technical here, now we have to understand practically what we are claiming analytically. We must create algorithms to represent the real world implications of our complex systems. Sometimes, like part #1, this is a learning experience through trial and error. However, many times it comes directly from our brains, translating abstractions of systems we see in the real world into the models of the phenomenon that can be parameterized.

I think many times people mean #3 when they say "learn" Netlogo. However, do not neglect #1 and #2! Constantly explore new models (#1) and try to understand how to think like a complexity scientist (#2). #3 will come to you naturally if you learn some Netlogo syntax and then focus on exploring solutions.

Good luck!

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[James Steiner]

Michael,

That was really interesting and insightful!

To view this discussion on the web visit https://groups.google.com/d/msgid/netlogo-users/CAFkCkGc2nCcCUS_338SpQLmW-FVSma%2B4h%2B3F-xt4eddaGye0XQ%40mail.gmail.com.

[Michael Tamillow]

Thanks James!

Sent from my iPhone

On Sep 26, 2022, at 2:01 PM, James Steiner <grego...@gmail.com> wrote:



[John Chen]

Hi friend - assume from your nickname, have you already used Scratch before?

On Mon, Sep 26, 2022 at 3:53 PM Scratch Cat (Scratchy) <maaha...@gmail.com> wrote:

Can you teach me NetLogo? I do not know how to use it.

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[Maahay Gardezi]

Yes, I did.