NetLogo
| NetLogo | |
|---|---|
| Paradigms : | Procedural , multi-agent simulation |
| Publishing year: | 1999 |
| Developer: | Uri Wilensky |
| Current version : | 6.1.1 (September 26, 2019) |
| Influenced by: | Logo , StarLogo |
| Operating system : | Platform independent ( Java ) |
| License : | GPL |
| http://ccl.northwestern.edu/netlogo/ | |
NetLogo is a multi-agent programming language with an integrated modeling environment. It was developed in the spirit of Logo (programming language) . The idea was to offer low entry difficulties while meeting the requirements of advanced developers.
NetLogo is particularly suitable for modeling complex systems over time. Modelers can give instructions to hundreds or thousands of " agents ", each working independently. This makes it possible to study the relationship between the behavior of individuals at the micro level and the patterns at the macro level that result from their interaction. NetLogo enables users to open simulations, "play" with them and observe their behavior under different conditions. It is also an authoring environment that enables you to create your own models.
The supplied "Models Library" consists of a large collection of ready-made simulations that can be used and modified. These simulations address content in the natural and social sciences including biology, medicine, physics, chemistry, math, computer science, economics, and social psychology.
This free and open source software under the GPL license is being developed at Northwestern University 's Center for Connected Learning and Computer-Based Modeling. The development is funded by the National Science Foundation and others. NetLogo is written in Scala and Java and runs on the Java Virtual Machine.
Examples
WolfSheepPredation
A simple multi-agent model in NetLogo is the wolf-sheep model, which is shown in the screenshot. It models the population growth of a predator-prey system and exists in two variants:
In the first variant, wolves and sheep wander randomly through the landscape, while the wolves look for sheep to hunt. Every step costs the wolves energy and they have to eat sheep to replenish their energy. When they run out of energy, they die. So that the population can continue to live, there is a fixed probability for every wolf and every sheep to reproduce at every time step. In this variation, there is an "infinite" amount of grass, so that sheep always have enough to eat. Sheep do not lose energy when eating or moving. This variation creates interesting population dynamics, but is ultimately unstable.
The second variant, the "Sheep-Wolf-Grass" version, models not only wolves and sheep but also grass (green). The behavior of the wolves is identical to the first variant, but this time the sheep have to eat grass to maintain their energy - if they run out of energy they die. As soon as the grass is eaten, it only grows back after a certain period of time. This variation is more complex than the first, but it is generally stable. The agreement with the classic Lotka Volterra population fluctuations is higher.
TrafficGrid
This is the right angle road traffic model of a city. It can be used to control traffic lights and global variables such as the speed limit and the number of vehicles and to investigate traffic dynamics.
With every step the cars try to move forward at their current speed. If their current speed is below the speed limit and there is no car in front of them, they accelerate. If there is a slower car in front of them, they will adjust to the speed of the slower car and decelerate. They stop in front of a red light or another parked car.
The traffic lights can change automatically with each cycle.
Web links
- CCL homepage
- NetLogo discussion group for users hosted by Google
- NetLogo developer discussion group hosted by Google
Individual evidence
- ↑ NetLogo Models Library: Wolf Sheep Predation. Retrieved November 27, 2018 .
- ↑ NetLogo Models Library: Traffic Grid. Retrieved November 27, 2018 .