NetLogo User Community Models

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## ACKNOWLEDGMENT

This model is originated from Chapter One of the book "Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo", by Uri Wilensky & William Rand.

* Wilensky, U. & Rand, W. (2015). Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo. Cambridge, MA. MIT Press.

I have **further modified and heavily commented** the model for learning NetLogo and Complexity concepts. I have made **both Chinese and English vdieo tutorials** on how to code up this model and analyse what this model generate. You are welcome to follow the tutorials while playing the model. https://github.com/EmbraceLife/shendusuipian/issues/50

## WHAT IS IT?

In this model, a colony of ants forages for food. Though each ant follows a set of simple rules, the colony as a whole acts in a sophisticated way.

## HOW IT WORKS

When an ant finds a piece of food, it carries the food back to the nest, dropping a chemical as it moves. When other ants "sniff" the chemical, they follow the chemical toward the food. As more ants carry food to the nest, they reinforce the chemical trail.

## HOW TO USE IT

Click the SETUP button to set up the ant nest (in violet, at center) and three piles of food. Click the GO button to start the simulation. The chemical is shown in a green-to-white gradient.

The EVAPORATION-RATE slider controls the evaporation rate of the chemical. The DIFFUSION-RATE slider controls the diffusion rate of the chemical.

If you want to change the number of ants, move the POPULATION slider before pressing SETUP.

## THINGS TO NOTICE

The ant colony generally exploits the food source in order, starting with the food closest to the nest, and finishing with the food most distant from the nest. It is more difficult for the ants to form a stable trail to the more distant food, since the chemical trail has more time to evaporate and diffuse before being reinforced.

Once the colony finishes collecting the closest food, the chemical trail to that food naturally disappears, freeing up ants to help collect the other food sources. The more distant food sources require a larger "critical number" of ants to form a stable trail.

The consumption of the food is shown in a plot. The line colors in the plot match the colors of the food piles.

## EXTENDING THE MODEL

Try different placements for the food sources. What happens if two food sources are equidistant from the nest? When that happens in the real world, ant colonies typically exploit one source then the other (not at the same time).

In this model, the ants always "know" where the nest is: when they want to go back to the nest, they just turn towards the center of the world (using `facexy 0 0`). Real ants use a variety of different approaches to find their way back to the nest. Try to implement some alternative strategies.

The ants only respond to chemical levels between 0.05 and 2. The lower limit is used so the ants aren't infinitely sensitive. Try removing the upper limit. What happens? Why?

In the `uphill-chemical` procedure, the ant "follows the gradient" of the chemical. That is, it "sniffs" in three directions, then turns in the direction where the chemical is strongest. You might want to try variants of the `uphill-chemical` procedure, changing the number and placement of "ant sniffs."

## NETLOGO FEATURES

The built-in `diffuse` primitive lets us diffuse the chemical easily without complicated code.

The primitive `patch-right-and-ahead` is used to make the ants smell in different directions without actually turning.

## RELATED MODELS

This model is a slight modification of the Ants models in the Biology section of the NetLogo models library.

## CREDITS AND REFERENCES

This model is a simplified version of:

* 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.

## HOW TO CITE

This model is part of the textbook, “Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo.”

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

For the model itself:

* Wilensky, U. (1997). NetLogo Ants Simple model. http://ccl.northwestern.edu/netlogo/models/AntsSimple. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, 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.

Please cite the textbook as:

* Wilensky, U. & Rand, W. (2015). Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo. Cambridge, MA. MIT Press.

## 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 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.

This model was created 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.

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