NetLogo Models Library:
Sample Models/Biology

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BeeSmart Hive Finding

If you download the NetLogo application, this model is included. You can also Try running it in NetLogo Web

WHAT IS IT?

The BeeSmart Master model shows the swarm intelligence of honeybees during their hive-finding process. A swarm of tens of thousands of honeybees can accurately pick the best new hive site available among dozens of potential choices through self-organizing behavior.

The mechanism in this model is based on Honeybee Democracy (Seeley, 2010) with some modifications and simplifications. One simplification is that this model only shows scout bees—a 3-5% population of the whole swarm that is actively involved in the decision making process. Other bees are left out because they simply follow the scouts to the new hive when a decision is made. Leaving out the non-scouts reduces the computational load and makes this model visually clearer.

This model is also the first of a series of models in a computational modeling-based scientific inquiry curricular unit “BeeSmart”, designed to help high school and university students learn complex systems principles as crosscutting concepts in science learning. Subsequent models are coming soon.

HOW IT WORKS

At each SETUP, 100 scout bees are placed at the center of the view. Meanwhile, a certain number (determined by the “hive-number” slider) of potential hive sites are randomly placed around the swarm.

On clicking GO, initial scouts (the proportion of which are determined by the “initial-percentage” slider) fly away from the swarm in different directions to explore the surrounding space. They will explore the space for a maximum of “initial-explore-time.” If one scout stumbles upon a potential hive site, she inspects it. Otherwise, she goes back to the swarm and remains idle.

When a scout discovers a potential hive site, she inspects it to learn its location, color, and quality. Then she flies back to the swarm to advertise the site through waggle dances. The better the quality of the hive, the longer the scouts dance, the easier these dances are seen by idle bees in the swarm, and the more likely idle bees follow the dances to inspect the advertised hive site. After a newly joined bee’s inspection of the advertised site, the new bee flies back to the swarm and expresses her own opinions about the site through waggle dances. Bees revisit the sites they advocated, but their interests in the site decline after each revisit. Advertising for different sites continues in parallel in the swarm, but high quality sites attract more and more bees while low quality ones are gradually ignored.

When bees on a certain hive site observe a certain number of bees on the same site, or, in other words, when the “quorum” is reached, they fly back to the swarm and start to “pipe” to announce that a decision has been made. Any bee that hears the piping will also pipe, which causes the piping to spread across the swarm quickly. When all the bees are piping, the whole swarm takes off to move to the winning hive site and the model stops.

Typically, an initial scout goes through the states of “discover”-> “inspect-hive”-> “go-home”-> “dance”-> “re-visit”-> “pipe”; and non-initial scouts follow a slightly different sequence of states: “watch-dance”-> “re-visit” -> “inspect-hive”-> “go-home”-> “dance”-> “re-visit”-> “pipe”.

HOW TO USE IT

Use the sliders to define the initial conditions of the model. The default values usually guarantee a successful hive finding, but users are encouraged to change these settings and see how each parameter affects the process.

Click SETUP after setting the parameters by the sliders. Then click GO and observe how the phenomenon unfolds. Toggle the “Show/Hide Dance Path” button to show or hide the waggle dance paths. Use the “Show/Hide Scouts” button to hide the bees if they block your view of the dance paths.

THINGS TO NOTICE

Notice the three plots on the right hand of the model:

The “committed” plot shows the number of scouts that are committed to inspecting and advocating for each hive site; The “on-site” plot shows the count of bees on each site; The “watching vs. working” plot shows the change in numbers of idle and working bees.

Observe how information about multiple sites is brought to the swarm at the center of the view and how preference of the swarm changes over time.

Notice whether the timing of discovering the best hive site affects the swarm’s decision.

Zoom in and compare the “enthusiasm” of dances for high quality sites with those for low quality ones. Bees not only dance longer but also more enthusiastically (or faster, in this model, when they are making turns) for higher quality sites.

THINGS TO TRY

Right click any scout and choose “Watch” from the right-click menu. A halo would appear around the scout to help you keep track of its movement.

Set sliders to different values and observe how these parameters affect the dynamic of the process.

Use the speed slider at the top of the model to slow down the model and observe the waggle dances.

Use “Control +” or “Command +” to zoom in and see the colors of the bees.

EXTENDING THE MODEL

This model shows the honeybees’ hive-finding phenomenon as a continuous process. However, in reality, this process may last a few days. Bees do rest over night. Weather conditions may also affect this process. Adding these factors to the model can make it more accurately represent the phenomenon in the real world.

Currently, Site qualities cannot be controlled from the interface. Some input interface elements can be added to enable users to specify the quality of each hive.

NETLOGO FEATURES

This model is essentially a state machine. Bees behave differently at different states. Command tasks are heavily used in this model to simplify the shifts between states and to enhance the performance of the model.

The pens in the plots are dynamically generated temporary plot pens, which match the number of hive sites that are determined by users.

The dance patterns are dynamically generated, which show the direction, distance, and quality of the hive advertised.

RELATED MODELS

Wilensky, U. (1997). NetLogo Ants model. http://ccl.northwestern.edu/netlogo/models/Ants. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Wilensky, U. (2003). NetLogo Honeycomb model. http://ccl.northwestern.edu/netlogo/models/Honeycomb. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

CREDITS AND REFERENCES

Seeley, T. D. (2010). Honeybee democracy. Princeton, NJ: Princeton University Press.

Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL.

HOW TO CITE

If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.

For the model itself:

• Guo, Y. and Wilensky, U. (2014). NetLogo BeeSmart Hive Finding model. http://ccl.northwestern.edu/netlogo/models/BeeSmartHiveFinding. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Please cite the NetLogo software as:

• Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

COPYRIGHT AND LICENSE

Copyright 2014 Uri Wilensky.

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu.

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