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NetLogo
NetLogo
5.0
0.0
NetLogo free download for Mac

NetLogo

Version 6.3.0

Modeling environment for simulating natural and social phenomena.

5.0
Based on 1 user rateRead reviews & comments
Free
Absolutely Free

NetLogo overview

NetLogo is a programmable modeling environment for simulating natural and social phenomena. It is particularly well suited for modeling complex systems developing over time. Modelers can give instructions to hundreds or thousands of independent "agents" all operating concurrently. This makes it possible to explore the connection between the micro-level behavior of individuals and the macro-level patterns that emerge from the interaction of many individuals.

NetLogo lets students open simulations and "play" with them, exploring their behavior under various conditions. It is also an authoring environment which enables students, teachers and curriculum developers to create their own models. NetLogo is simple enough that students and teachers can easily run simulations or even build their own. And, it is advanced enough to serve as a powerful tool for researchers in many fields.

NetLogo has extensive documentation and tutorials. It also comes with a Models Library, which is a large collection of pre-written simulations that can be used and modified. These simulations address many content areas in the natural and social sciences, including biology and medicine, physics and chemistry, mathematics and computer science, and economics and social psychology. Several model-based inquiry curricula using NetLogo are currently under development.

Note: While the software is classified as free, it is actually donationware. Please consider making a donation to help support development.

What’s new in version 6.3.0

Updated on Jan 25 2023

Bug Fixes and Changes
  • The models library will correctly display when NetLogo is set to a language other than English.
  • The log4j library has been removed from NetLogo. Logging is now configured from the NetLogo preferences dialog. The output is in JSON text file format. See the Logging docs for more information.
  • BehaviorSpace experiments can now also be run from a terminal or command console using the NetLogo_Console app with NetLogo’s bundled Java by using the --headless flag. See the BehaviorSpace documentation for more information and examples. This avoids the need to install and configure a separate Java runtime to use the netlogo-headless.sh script, which remains bundled for those who require it.
  • BehaviorSpace output files are now chosen directly during run setup instead of separate prompts at the run start. This simplifies the setup process and resolves a bug where the runs would not occur on macOS.
  • The System Dynamics Modeler UI has some small improvements.
  • Fixed a bug where slider widgets would allow initial values outside of their range when changing the limits.
  • Better handle asymptotic values for tan with a proper error message.
  • NetLogo will now correctly handle running map or foreach when no lists are given.
  • When an anonymous task that uses let variables is displayed as a string it will now include those variable names.
  • Reporters used in concise task syntax no longer give the wrong result when used with fewer arguments than their default.
  • The models library location will be correctly set when using GUI scripts.
  • Behaviorsearch now sets a flag to alert extensions that they are being run without a UI so that extension code can adjust appropriately.
Extension Updates
  • GoGo: Improve newer GoGo board compatibility and improve the stability of the extension.
  • LevelSpace: Eliminate crashes when the controlling API is used to run NetLogo without a UI.
  • Profiler: The profiler:data results are now given in milliseconds instead of nanoseconds, matching the other primitives in the extension.
  • Python: Improvements in how the extension searches for the Python binaries when they aren’t specified via the configuration menu.
  • Vid: Update backing libraries to try to improve stability and usability on macOS and Windows.
Documentation Updates
  • Update the system requirements to include Windows 11.
  • Fixed a bad link to the extension API version 5 to 6 transition guide.
  • Added a FAQ entry on how to save random seeds from runs.
Models Library Changes
New Sample Models:
  • Slime Mold Network
  • Virus Using Discrete Event Simulator (cross-listed in code examples for time extension)
  • Distribution Center Discrete Event Simulator (cross-listed in code examples for time extension)
  • Hydrogen Gas Production
  • CA 1D-Squaring
  • Molecular Dynamics Lennard-Jones
New Curricular Models:
  • CT-STEM
  • Habitat Preference
New Code Examples:
  • time: Logotimes Example
  • time: Discrete Event Whack-a-Mole
Sample Model Changes
  • Taxi Cabs: Fixed Dongping Zhang’s name in the credits.
  • Turbulence: Cross-listed under CS/CA.
  • Tree Simple: Changed init-x slider min/max to -100/100. Before the range was -125/125, which caused an error.
  • Traffic Basic: Changed speed-limit and speed-min from agent variables to be globals.
  • Urban Suite - Cells: Renamed the go * 80 button to go * 40, reflecting its actual effect.
  • CA 1D Rule 30 - Improved the info tab to explain how Rule 30 has been used as random number generator.
Curricular Models Changes:
  • PNoM 4 Virtual Syringe Force Graph: fixed a bug that produced an error message.
  • Kidney Reabsorption: Some improvements to the info tab.
Newly Verified Models
  • The suite of prisoner’s dilemma models have been in the models library for a long time but were previously “unverified.” They have been reviewed/verified and moved into the main Social Science folder.

Information

License

Free

Size

350 MB

Downloads

16955

App requirements

  • Intel 64
  • OS X 10.8.3 or later
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Eyecapture
Eyecapture
Sep 12 2009
4.1rc4
5.0
Sep 12 2009
5.0
Version: 4.1rc4
This is fantastic! The included sample simulations offer unique insights into many questions such as: Do bird flocks have a leader? How much would you stand to save by upgrading the insulation of your home? How do traffic jams develop and resolve? Watch as hundreds or even thousands of simulated animals, molecules, cells or guests at a party interact. Turn a knob or push a slider and the patterns change as each individual element in the simulation alters its behavior. There is probably no better illustration of the ways complex behavior can arise out of nothing but large numbers of independent actors each doing its own thing by following simple rules. Incredibly mind-expanding stuff!
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