This explorable illustrates how a school of fish can collectively find an optimal location, e.g. a dark, unexposed region in their environment simply by light-dependent speed control. The explorable is based on the model discussed in Flock’n Roll, which you may want to explore first.

This is how it works:

The swarm here consists of 100 individuals. Each individual moves around at a constant speed and changes direction according to three rules:

1. Individuals try to align their direction with others in a small alignment radius,
2. they try to move towards the center of mass of others in an attraction radius,
3. they also wiggle around a bit, changing their heading randomly

You can change these parameters with the corresponding sliders.

Finding safe regions

The key difference to the system discussed in Flock’n Roll is that here slowly moving dark zones provide safe regions that the swarm seeks. This is accomplished collectively here by a very simple mechanism. Individuals move at a larger speed (speed in the light-slider) when they are exposed to light, they slow down when they are in the dark (speed in the dark-slider), they do not move towards the dark region or away from the light, they can only sense brightness where they are and adjust their speed accordingly.

The combination of light-dependent speed and collective cohesion, in certain parameter ranges, ensures that most of the time the swarm remains in the safe dark zones.

You can use the toggle Collective Behavior to switch off the swarm interactions temporarily to confirm that their interactions are essential for finding the dark zones. With the Dark Zones toggle you can temporarily remove the safe regions.

Try this

You can play with the speed variables to see what combination of speeds is most effective in terms of finding the safe zones.

When you increase the aligment radius, individuals tend to move in vortex patterns which makes it a bit more difficult to remain in the dark zones.

More Information

• Andrew Berdahl, Colin J. Torney, Christos C. Ioannou, Jolyon J. Faria, Iain D. Couzin, Emergent Sensing of Complex Environments by Mobile Animal Groups, Science, Vol. 339, Issue 6119, pp. 574-576

• Andrew M Hein, Sara Brin Rosenthal, George I Hagstrom, Andrew Berdahl, Colin J Torney, Iain D Couzin, The evolution of distributed sensing and collective computation in animal populations, eLife 2015;4:e10955