NetLogo多主体建模入门

里面有些代码都前后不一致，也有打错了的。70页有个赋值语句里有个保留词写的是 turtles-here，到后面讲解的时候同样的位置就突然变成turtles，少了-here，不知道为什么前后不一致的，也没讲解或者任何的说明，如果两种表达在语法上都是没错的，但做出来模型就完全不一样，离谱。

还有不少那种语焉不详、解释不清，讲解不明的地方，我寻思这书也不是国外译介的，中国人讲中国话都讲不好。

讲真，不知道前言里那些极力推荐这本书的砖家学者们有没有真正翻开看过，呵呵。

## 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

* Flocking - Alternative Visualizations

## 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 https://web.archive.org/web/20210818090425/http://www.red3d.com/cwr/boids/.

## 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:

* 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.

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 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 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 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.

<!-- 1998 2002 -->

生命游戏 这个模型下的笔记，待考。

Is there a “critical density” - one at which all change and motion stops/eternal motion begins?

这个density指的是初始的密度。模型默认为35%，在帮助文件中有问临界密度。不知道什么意思。

原代码

globals [

erasing? ;; is the current draw-cells mouse click erasing or adding?

]

patches-own [

living? ;; indicates if the cell is living

live-neighbors ;; counts how many neighboring cells are alive

]

to setup-blank

clear-all

ask patches [ cell-death ]

reset-ticks

end

to setup-random

clear-all

ask patches

[ ifelse random-float 100.0 < initial-density

[ cell-birth ]

[ cell-death ] ]

reset-ticks

end

to cell-birth

set living? true

set pcolor fgcolor

end

to cell-death

set living? false

set pcolor bgcolor

end

to go

ask patches

[ set live-neighbors count neighbors with [living?] ]

;; Starting a new "ask patches" here ensures that all the patches

;; finish executing the first ask before any of them start executing

;; the second ask. This keeps all the patches in synch with each other,

;; so the births and deaths at each generation all happen in lockstep.

ask patches

[ ifelse live-neighbors = 3

[ cell-birth ]

[ if live-neighbors != 2

[ cell-death ] ] ]

tick

end

to draw-cells

ifelse mouse-down? [

if erasing? = 0 [

set erasing? [living?] of patch mouse-xcor mouse-ycor

]

ask patch mouse-xcor mouse-ycor [

ifelse erasing? [

cell-death

] [

cell-birth

]

]

display

] [

set erasing? 0

]

end

; Copyright 1998 Uri Wilensky.

; See Info tab for full copyright and license.