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第1行： − 此词条属于[[NetLogo模型汇总]]项目，项目旨在汉化NetLogo Web的模型手册。 − − 原文链接：[http://ccl.northwestern.edu/netlogo/models/Flocking Flocking] − + 第11行：
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第280行： − − == 参考文献 == − 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 <nowiki>https://web.archive.org/web/20210818090425/http://www.red3d.com/cwr/boids/</nowiki>. − − − 这个模型的灵感来自克雷格·雷诺兹发明的Boids模拟。我们在这里使用的算法与原始Boids算法大致相似，但并不相同。算法的具体细节并不重要——只要你拥有对齐、分离和靠近，你便能够获得类似于Reynolds最初模型所创造的群体行为。有关Boids的信息请访问https://web.archive.org/web/20210818090425/<nowiki>http://www.red3d.com/cwr/boids/。</nowiki> − For the model itself: − − − Please cite the NetLogo software as:
无编辑摘要
[[文件:Flocking.png|缩略图]]
[[文件:Flocking.png|缩略图]]
== 鸟群模型 ==
== 鸟群模型 ==
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.
This model is an attempt to mimic the [http://ccl.northwestern.edu/netlogo/models/Flocking 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（运行规则） ==
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/ Boids].
这个模型的灵感来自克雷格·雷诺兹发明的Boids模拟。我们在这里使用的算法与原始Boids算法大致相似，但并不相同。算法的具体细节并不重要——只要你拥有对齐、分离和靠近，你便能够获得类似于Reynolds最初模型所创造的群体行为。有关鸟群算法，请参见百科词条：[[鸟群算法 Boids]]。
== 运行规则 ==
The birds follow three rules: "alignment", "separation", and "cohesion".
The birds follow three rules: "alignment", "separation", and "cohesion".
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=== THINGS TO TRY（你可以试一试） ===
==== THINGS TO TRY（你可以试一试） ====
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.
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.
注意，取鸟群的平均飞行方向需要使用<code>subtract-headings</code>语句。单纯的减去数字或者取平均值并不能得到结果，在NetLogo默认设定中这些数字一旦达到360度，标朝向会自动转回0。
注意，取鸟群的平均飞行方向需要使用<code>subtract-headings</code>语句。单纯的减去数字或者取平均值并不能得到结果，在NetLogo默认设定中这些数字一旦达到360度，标朝向会自动转回0。
==编者推荐==
===集智相关课程===
[[File:Auklet_flock_Shumagins_1986.jpg|300px|thumb|[https://swarma.org/?p=16504 张江：乌合之众还是群智涌现？鸟群知道答案]|链接=https://wiki.swarma.org/index.php/%E6%96%87%E4%BB%B6:Auklet_flock_Shumagins_1986.jpg]]
* [https://campus.swarma.org/course/1104 透过人工鸟群Boid模型学习List的使用]
讲师：[https://wiki.swarma.org/index.php/%E5%BC%A0%E6%B1%9F 张江](北师大系统科学学院教授、博士生导师，集智俱乐部、集智学园创始人。)
本课程通过数个案例教会大家如何去动手搭建一个多主体仿真模型，以及如何利用NetLogo去实现。从生命游戏到人工鸟群，从模拟经济系统到病毒沿网络的传播，通过循序渐进的案例，该课程带你逐步走入NetLogo多主体建模的神奇世界。
===书籍推荐===
[[File:复杂.jpg|200px|thumb|right|《复杂》封面|链接=https://wiki.swarma.org/index.php/%E6%96%87%E4%BB%B6:%E5%A4%8D%E6%9D%82.jpg]]
*[https://vdisk.weibo.com/s/BTLfj870SYIar 《复杂》 梅拉妮·米歇尔]
蚂蚁在组成群体时为何会表现出如此的精密性和具有目的性？数以亿计的神经元是如何产生出像意识这样极度复杂的事物？是什么在引导免疫系统、互联网、全球经济和人类基因组等自组织结构？这些都是复杂系统科学尝试回答的迷人而令人费解的问题的一部分。理解复杂系统需要有全新的方法，需要超过传统的科学还原论，并重新划定学科的疆域。借助于圣塔菲研究所的工作经历和交叉学科方法，复杂系统的前沿科学家米歇尔在《复杂》一书中，以清晰的思路介绍了复杂系统的研究，横跨生物、技术和社会学等领域，并探寻复杂系统的普遍规律。与此同时，她还探讨了复杂性与进化、人工智能、计算、遗传、信息处理等领域的关系。
===文章推荐===
* [https://swarma.org/?p=16504 张江：乌合之众还是群智涌现？鸟群知道答案]
生命如何起源，智能如何涌现，因果如何反转，复杂谜题，引人深思。2019年7月13日，集智俱乐部创始人[https://wiki.swarma.org/index.php/%E5%BC%A0%E6%B1%9F 张江]教授在混沌大学授课，详细解读了复杂系统中的混沌、涌现与进化，此文整理自课堂内容。
* [https://zhuanlan.zhihu.com/p/97717680 超越简单规则——用图神经网络对复杂系统进行自动建模]
近期，由北京师范大学张江团队发表的文章《A general deep learning framework for network reconstruction and dynamics learning》在期刊Applied Network Science上刊登，这篇文章提出了一种基于深度学习的数据驱动模型，可以从节点的时间演化数据中重构出网络结构，并且学习到系统的动力学。本文是第一作者张章对该文章内容的解读。
===课程推荐===
*[https://campus.swarma.org/course/1095 NetLogo多主体建模入门]
::本课程通过数个案例教会大家如何去动手搭建一个多主体仿真模型，以及如何利用NetLogo去实现。从生命游戏到人工鸟群，从模拟经济系统到病毒沿网络的传播，通过循序渐进的案例，该课程带你逐步走入NetLogo多主体建模的神奇世界。
*[https://campus.swarma.org/course/596 生物中的多主体模型]
::本课程将视线转移到生物学领域，展现计算机模拟在生物学中的应用。认识自然现象，我们可以从物理、数学、生物、天文、化学等众多角度去解读，那么怎样将众多的知识综合起来转化为可以用计算机模拟的语言哪？本节课将通过一个模型案例来帮助我们打开思路，更好的去描述和模拟生物现象。
== 相关模型 ==
== 相关模型 ==
* Flocking Vee Formation
* Flocking Vee Formation
* Flocking - Alternative Visualizations
* Flocking - Alternative Visualizations
== Reference ==
== Reference ==
* Wilensky, U. (1998). NetLogo Flocking model. <nowiki>http://ccl.northwestern.edu/netlogo/models/Flocking</nowiki>. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
* Wilensky, U. (1998). NetLogo Flocking model. <nowiki>http://ccl.northwestern.edu/netlogo/models/Flocking</nowiki>. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
* Wilensky, U. (1999). NetLogo. <nowiki>http://ccl.northwestern.edu/netlogo/</nowiki>. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
* Wilensky, U. (1999). NetLogo. <nowiki>http://ccl.northwestern.edu/netlogo/</nowiki>. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.