Slime

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WHAT IS IT?

This project is inspired by the aggregation behavior of slime-mold cells. It shows how creatures can aggregate into clusters without the control of a "leader."

In this example, each turtle drops a chemical pheromone (shown in green). The turtles also "sniff" ahead, trying to follow the gradient of other turtles' chemicals. Meanwhile, the patches diffuse and evaporate the pheromone. Following these simple, decentralized rules, the turtles aggregate into clusters.

HOW TO USE IT

Click the SETUP button to set up a collection of slime-mold cells. Click the GO button to start the simulation.

The POPULATION slider controls the number of slime mold cells in the simulation. Changes in the POPULATION slider do not have any effect until the next SETUP command.

The other sliders affect the way turtles move. Changes to them will immediately affect the model run.

SNIFF-THRESHHOLD -- The minimum amount of chemical that must be present in a turtle's patch before the turtle will look for a chemical gradient to follow. This parameter causes the turtles to aggregate only when there are enough other cells nearby. The default value is 1.0.

SNIFF-ANGLE -- The amount, in degrees, that a turtle turns to the left and right to check for greater chemical concentrations. The default value is 45.

WIGGLE-ANGLE -- The maximum amount, in degrees, that a turtle will turn left or right in its random movements. When WIGGLE-ANGLE is set to zero, the turtle will remain at the same heading until it finds a chemical gradient to follow. The default value is 40.

WIGGLE-BIAS -- The bias of a turtle's average wiggle. When WIGGLE-BIAS = 0, the turtle's average movement is straight ahead. When WIGGLE-BIAS > 0, the turtle will tend to move more right than left. When BIAS < 0, the turtle will tend to move more left than right. The default value is 0.

There are several other critical parameters in the model that are not accessible by sliders. They can be changed by modifying the code in the procedures window. They are:

• the evaporation rate of the chemical -- set to 0.9
• the diffusion rate of the chemical -- set to 1
• the amount of chemical deposited at each step -- set to 2

THINGS TO NOTICE

With 100 turtles, not much happens. The turtles wander around dropping chemical, but the chemical evaporates and diffuses too quickly for the turtles to aggregate.

With 400 turtles, the result is quite different. When a few turtles happen (by chance) to wander near one another, they create a small "puddle" of chemical that can attract any number of other turtles in the vicinity. The puddle then becomes larger and more attractive as more turtles enter it and deposit their own chemicals. This process is a good example of positive feedback: the more turtles, the larger the puddle; and the larger the puddle, the more likely it is to attract more turtles.

THINGS TO TRY

Try different values for the SNIFF-THRESHOLD, SNIFF-ANGLE, WIGGLE-ANGLE, and WIGGLE-BIAS sliders. How do they affect the turtles' movement and the formation of clumps?

Change the SNIFF-ANGLE and WIGGLE-ANGLE sliders after some clumps have formed. What happens to the clumps? Try the same with SNIFF-THRESHOLD and WIGGLE-BIAS.

EXTENDING THE MODEL

Modify the program so that the turtles aggregate into a single large cluster.

How do the results change if there is more (or less) randomness in the turtles' motion?

Notice that the turtles only sniff for chemical in three places: forward, SNIFF-ANGLE to the left, and SNIFF-ANGLE to the right. Modify the model so that the turtles sniff all around. How does their clustering behavior change? Modify the model so that the turtles sniff in even fewer places. How does their clustering behavior change?

What "critical number" of turtles is needed for the clusters to form? How does the critical number change if you modify the evaporation or diffusion rate?

Can you find an algorithm that will let you plot the number of distinct clusters over time?

NETLOGO FEATURES

Note the use of the patch-ahead, patch-left-and-ahead, and patch-right-and-ahead primitives to do the "sniffing".

RELATED MODELS

Ants uses a similar idea of creatures that both drop chemical and follow the gradient of the chemical.

HOW TO CITE

If you mention this model in a publication, we ask that you include these citations for the model itself and for the NetLogo software:

• Wilensky, U. (1997). NetLogo Slime model. http://ccl.northwestern.edu/netlogo/models/Slime. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL.
• Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL.

COPYRIGHT AND LICENSE

Copyright 1997 Uri Wilensky.

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit http://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.

This model was created as part of the project: CONNECTED MATHEMATICS: MAKING SENSE OF COMPLEX PHENOMENA THROUGH BUILDING OBJECT-BASED PARALLEL MODELS (OBPML). The project gratefully acknowledges the support of the National Science Foundation (Applications of Advanced Technologies Program) -- grant numbers RED #9552950 and REC #9632612.

This model was developed at the MIT Media Lab using CM StarLogo. See Resnick, M. (1994) "Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds." Cambridge, MA: MIT Press. Adapted to StarLogoT, 1997, as part of the Connected Mathematics Project.

This model was converted to NetLogo as part of the projects: PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN CLASSROOMS and/or INTEGRATED SIMULATION AND MODELING ENVIRONMENT. The project gratefully acknowledges the support of the National Science Foundation (REPP & ROLE programs) -- grant numbers REC #9814682 and REC-0126227. Converted from StarLogoT to NetLogo, 2000.

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