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Hot Topics: Biological Self-Organization
Summer 2013
Exploration 4. What special properties, if any, distinguish flock “leaders” from other birds in
the flock? (To help answer this question, Control-click on a single bird at the head of a
flock to bring up a menu of options. Choose the last option (“turtle i”), then select “watch turtle i”. This will create a circle around that bird, letting you track its movements more
easily. To remove the circle, Control-click on the same bird and choose reset-­‐perspective.)
Suggested answer: There is no intrinsic difference between flock leaders and other birds. As
the simulation runs, flocks will split and merge, with different birds emerging as (temporary)
leaders. Each bird’s position within the flock emerges purely from local interactions between
interchangeable agents, a defining property of self-organizing systems.
Exploration 5. Working in pairs, choose some aspect of the system to study further. For
example, you might explore the effect of a particular variable on the birds’ behavior, or
analyze the change in some property over time. Write down the question you have chosen
to research, then take 15-20 minutes to study that question using the model. Clearly record
your procedures, results, and inferences. Then share your findings with the entire class as a
one-minute presentation.
Suggested answer: Results will depend on the questions chosen. However, each group
should produce a clearly stated question, an appropriate experimental design, and a general
statement of their results. For example, students exploring how visual range affects flock size
might run the model for values of vision ranging from 0 to 10 patches. They might then
report that no flocking occurs when vision ≤ 1.0 patches, but that flock size rapidly increases
thereafter, eventually producing a single large flock when vision ≥ approximately 8 patches.
They might also note that the simulation runs more slowly for larger values of vision (because
the model must make more calculations as each bird sees more and more of its neighbors).
VII. Extensions
Once you have worked with the Flocking model for a little while, you may want to customize
the display, add more complex and realistic behaviors, or explore other models of self-organizing
systems. NetLogo’s built-in tutorials, user manual, and code examples provide many resources to
help you do so. A few particularly useful features:
• You can add plots and controls using the toolbar on the
Interface tab (see screenshot at right). For example, add
a switch to turn a particular property on or off, or put in a
monitor to output the value of a specific variable within
the model. Plots can be customized to display frequency
histograms or to track one or more numeric variables
over time, using pre-built code examples from the
Models Library (Histogram Example and Tutorial 3,
respectively).
• The Code Examples section of the Models Library also
contains pre-built examples of specific agent behaviors
that may be useful when modeling particular biological
systems. You can copy and paste this code into your own
model, then modify it as needed. For example, when an
agent in the Flocking model moves past the right-hand
edge of the simulated world, it reappears on the left-hand
edge (i.e., the edges “wrap around”). If you instead want agents in your model to bounce like
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