Flocking Migration
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REFLECTION
With respect to exploring the models, we wanted to find a model that would allow us to explore how creating instances would affect a network of interacting parts/objects. We deliberated Preferential Attachment and Flocking. We decided that flocking would allow us to manipulate the network in the best way given the autonomous parts (birds) versus interconnected nodes.
We modified Flocking model to respond to a temperature reading from an external sensor in order to simulate an attractant versus repellant element in the environment. We decided to track the encounter by having the birds change color once they pass through a set patch and report a hot or cold encounter. As the birds sense a cooling, the huddle together, change to purple color, and then look for nearest flockmates. Birds who encounter the coldest temperature ranges turn white and move together to avoid the cooler box. Birds who encounter heat, change red and scatter.
WHAT IS IT?
This model is an attempt to mimic the flocking of birds. (The resulting motion also resembles schools of fish.) The flocks that appear in this model are not created or led in any way by special leader birds. Rather, each bird is following exactly the same set of rules, from which flocks emerge.
HOW IT WORKS
The birds follow three rules: "alignment", "separation", and "cohesion".
"Alignment" means that a bird tends to turn so that it is moving in the same direction that nearby birds are moving.
"Separation" means that a bird will turn to avoid another bird which gets too close.
"Cohesion" means that a bird will move towards other nearby birds (unless another bird is too close).
When two birds are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.
The three rules affect only the bird's heading. Each bird always moves forward at the same constant speed.
HOW TO USE IT
First, determine the number of birds you want in the simulation and set the POPULATION slider to that value. Press SETUP to create the birds, and press GO to have them start flying around.
The default settings for the sliders will produce reasonably good flocking behavior. However, you can play with them to get variations:
Three TURN-ANGLE sliders control the maximum angle a bird can turn as a result of each rule.
VISION is the distance that each bird can see 360 degrees around it.
THINGS TO NOTICE
Central to the model is the observation that flocks form without a leader.
There are no random numbers used in this model, except to position the birds initially. The fluid, lifelike behavior of the birds is produced entirely by deterministic rules.
Also, notice that each flock is dynamic. A flock, once together, is not guaranteed to keep all of its members. Why do you think this is?
After running the model for a while, all of the birds have approximately the same heading. Why?
Sometimes a bird breaks away from its flock. How does this happen? You may need to slow down the model or run it step by step in order to observe this phenomenon.
THINGS TO TRY
Play with the sliders to see if you can get tighter flocks, looser flocks, fewer flocks, more flocks, more or less splitting and joining of flocks, more or less rearranging of birds within flocks, etc.
You can turn off a rule entirely by setting that rule's angle slider to zero. Is one rule by itself enough to produce at least some flocking? What about two rules? What's missing from the resulting behavior when you leave out each rule?
Will running the model for a long time produce a static flock? Or will the birds never settle down to an unchanging formation? Remember, there are no random numbers used in this model.
EXTENDING THE MODEL
Currently the birds can "see" all around them. What happens if birds can only see in front of them? The in-cone
primitive can be used for this.
Is there some way to get V-shaped flocks, like migrating geese?
What happens if you put walls around the edges of the world that the birds can't fly into?
Can you get the birds to fly around obstacles in the middle of the world?
What would happen if you gave the birds different velocities? For example, you could make birds that are not near other birds fly faster to catch up to the flock. Or, you could simulate the diminished air resistance that birds experience when flying together by making them fly faster when in a group.
Are there other interesting ways you can make the birds different from each other? There could be random variation in the population, or you could have distinct "species" of bird.
NETLOGO FEATURES
Notice the need for the subtract-headings
primitive and special procedure for averaging groups of headings. Just subtracting the numbers, or averaging the numbers, doesn't give you the results you'd expect, because of the discontinuity where headings wrap back to 0 once they reach 360.
RELATED MODELS
- Moths
- Flocking Vee Formation
CREDITS AND REFERENCES
This model is inspired by the Boids simulation invented by Craig Reynolds. The algorithm we use here is roughly similar to the original Boids algorithm, but it is not the same. The exact details of the algorithm tend not to matter very much -- as long as you have alignment, separation, and cohesion, you will usually get flocking behavior resembling that produced by Reynolds' original model. Information on Boids is available at http://www.red3d.com/cwr/boids/.
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. (1998). NetLogo Flocking model. http://ccl.northwestern.edu/netlogo/models/Flocking. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
- 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 1998 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 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, 2002.
Comments and Questions
patches-own [ read-temp ] turtles-own [ flockmates ;; agentset of nearby turtles nearest-neighbor ;; closest one of our flockmates readyteam? ;; enough friends to migrate ] extensions [gogo] globals [ serial-port ;; different on different operating systems ] to setup clear-all ask patches [set pcolor SKY ] crt population [ set color yellow - 2 + random 7 ;; random shades look nice set size 1.5 ;; easier to see setxy random-xcor random-ycor ] reset-ticks ifelse length (gogo:ports) > 0 [ set serial-port user-one-of "Select a port:" gogo:ports ] [ user-message "There is a problem with the connection. Check if the board is on, and if the cable is connected. Otherwise, try to quit NetLogo, power cycle the GoGo Board, and open NetLogo again. For more information on how to fix connection issues, refer to the NetLogo documentation or the info tab of this model" stop ] gogo:open serial-port repeat 5 [ if not gogo:ping [ user-message "There is a problem with the connection. Check if the board is on, and if the cable is connected. Otherwise, try to quit NetLogo, power cycle the GoGo Board, and open NetLogo again. For more information on how to fix connection issues, refer to the NetLogo documentation or the info tab of this model"] ] gogo:talk-to-output-ports [ "a" "b" "c" "d"] end to test-connection carefully [ ifelse not gogo:ping [ user-message "There is a problem with the connection. Check if the board is on, and if the cable is connected. Otherwise, try to quit NetLogo, power cycle the GoGo Board, and open NetLogo again. For more information on how to fix connection issues, refer to the NetLogo documentation or the info tab of this model" ] [ user-message "GoGo Board connected and working!" ] ] [ user-message error-message stop ] end ; Public Domain: ; To the extent possible under law, Uri Wilensky has waived all ; copyright and related or neighboring rights to this model. to go let temp gogo:sensor 3 ask turtles [ flock ] ;; the following line is used to make the turtles ;; animate more smoothly. repeat 5 [ ask turtles [ fd 0.2 ] display ] ;; for greater efficiency, at the expense of smooth ;; animation, substitute the following line instead: ;; ask turtles [ fd 1 ] tick end ;;to coolerbox ;;set pcolor black ;;end to migrate let temp gogo:sensor 3 ask patches with [pxcor > 0 and pxcor < 16 and pycor > -8 and pycor < 8 ] [ set pcolor black set read-temp temp if read-temp > 600 and read-temp < 620 ;; cool [ ask turtles-here [ set color violet - 2 + random 4 flock ] ] if read-temp > 620 ;; coldest [ ask turtles-here [set color white rt 45] ] if read-temp < 600 ;; hot [ ask turtles-here [set color red - 2 + random 4 scatter ] ] ] end to goteam ;; set readyteam? count flockmates >= ( 2 ) set readyteam? count flockmates >= ( 2 ) ask turtles with [ readyteam? ] [set heading 180] ask turtles with [ not readyteam? ] [flock] end to scatter set heading random 360 rt 40 end to flock;; turtle procedure find-flockmates if any? flockmates [ find-nearest-neighbor ifelse distance nearest-neighbor < minimum-separation [ separate ] [ align cohere ] ] end to find-flockmates ;; turtle procedure set flockmates other turtles in-radius vision end to find-nearest-neighbor ;; turtle procedure set nearest-neighbor min-one-of flockmates [distance myself] end ;;; SEPARATE to separate ;; turtle procedure turn-away ([heading] of nearest-neighbor) max-separate-turn end ;;; ALIGN to align ;; turtle procedure turn-towards average-flockmate-heading max-align-turn end to-report average-flockmate-heading ;; turtle procedure ;; We can't just average the heading variables here. ;; For example, the average of 1 and 359 should be 0, ;; not 180. So we have to use trigonometry. let x-component sum [dx] of flockmates let y-component sum [dy] of flockmates ifelse x-component = 0 and y-component = 0 [ report heading ] [ report atan x-component y-component ] end ;;; COHERE to cohere ;; turtle procedure turn-towards average-heading-towards-flockmates max-cohere-turn end to-report average-heading-towards-flockmates ;; turtle procedure ;; "towards myself" gives us the heading from the other turtle ;; to me, but we want the heading from me to the other turtle, ;; so we add 180 let x-component mean [sin (towards myself + 180)] of flockmates let y-component mean [cos (towards myself + 180)] of flockmates ifelse x-component = 0 and y-component = 0 [ report heading ] [ report atan x-component y-component ] end ;;; HELPER PROCEDURES to turn-towards [new-heading max-turn] ;; turtle procedure turn-at-most (subtract-headings new-heading heading) max-turn end to turn-away [new-heading max-turn] ;; turtle procedure turn-at-most (subtract-headings heading new-heading) max-turn end ;; turn right by "turn" degrees (or left if "turn" is negative), ;; but never turn more than "max-turn" degrees to turn-at-most [turn max-turn] ;; turtle procedure ifelse abs turn > max-turn [ ifelse turn > 0 [ rt max-turn ] [ lt max-turn ] ] [ rt turn ] end ; Copyright 1998 Uri Wilensky. ; See Info tab for full copyright and license.
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