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Description of the simulation
In this simulation, you can see fish, that form swarms and avoid obstacles and predators. Basically, prey and predators perform an random walk. But there are
several special individual events and behaviors, that lead to the observed group behavior:
Every x steps, each prey fish updates a list of visible neighbors, which are all fish within a range given by the slider sensory-range. How often this update is performed is given by the slider called update-neighborhood-every.
It is only for speeding up the simulation, that the neighborhood gets sensed by each fish every time step.
After that, several random fishes are picked out from this sensed neighbored fishes. How much are picked is given by the slider accounted-fish.
Each of these picked fishes has some influence upon the focal fishes further moving direction. If the picked fish is too near, the fish works like a repellent
and the focal fish turns away. If the picked fish further away, the focal fish chooses a traveling direction parallel to those of the picked fish. If the picked fish is too far away, the focal fish turn toward the
picked fish, in order to decrease the distance.
The two sliders dist-repulsive and dist-parallel set the two borders between the three ranges of distances.
- If the distance < dist-repulsive, than the focal fish turns away
- if the distance is between dist-repulsive and dist-parallel, then the focal fish aligns to the picked fish
- if the distance > dist-parallel, then the focal fish turns towards the picked fish.
But the focal fish does not just pick one single fish from his neighborhood. How to deal with the information gathered from several picked (accounted) fishes ?
The solution is just building mean values. Each accounted fish results into a vector. The focal fish just averages all those vectors. When turning on the
slider latency, the vectors are not affecting the focal fish immediately. Again, we calculate weighted means with the current moving vector and the vectors suggested by the accounted neighboring fishes. The higher
the latency, the more weight is accounted to the current moving vector.
But the moving vector of all prey fish is not only influenced by other prey fish. Predator fishes work as extreme repellants, obstacles also work as
The slider randomness provides additional random input to this decision.
The predator fishes perform basically a random walk, but when prey fish come into their view, they turn towards them.
- Check how the number of actors (prey, predators, obstacles) changes the collective behavior.
- Check whether the number of fishes taken into account for the flocking decisions plays an important role or not.
- Check how the latency influences the movements of the swarm
- Test several combinations of dist-repulsive, dist-parallel and sensory-range and see, how different kinds of flocks are created (dense flocks,
The presented NetLogo simulation was written by:
Thomas Schmickl (2002), Department for Zoology, Karl-Franzens-University Graz, Austria, Europe, email@example.com, firstname.lastname@example.org
- Camazine S., Deneubourg J.-L., Franks N.R., Sneyd J., Theraulaz G. and Bonabeau E. (2001) Self-Organization in biological systems.
Princeton University Press.