TEDxZurich 2013
Nicolas Perony: Puppies! Now that I’ve got your attention, complexity theory
尼古拉斯·佩罗尼: 小狗狗！现在我吸引到你的注意了，复合性理论--尼古拉斯·佩罗尼
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动物行为并不复杂，但却是复合的。尼古拉斯·佩罗尼研究动物个体如何--不论是苏格兰梗犬，蝙蝠，还是猫鼬--遵循简单的规则，而共同产生出更大的行为模式。以及这种由简单性导致的复合性如何帮助它们在新情况出现时能够适应。
Nicolas Perony - Animal scientist
Nicolas Perony models the movement of animal groups to understand: what is the individual behavior that guides the behavior of the larger society? Full bio
Nicolas Perony models the movement of animal groups to understand: what is the individual behavior that guides the behavior of the larger society? Full bio
Double-click the English transcript below to play the video.
00:15
Science,
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科学，
00:16
science has allowed us to know so much
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科学让我们了解了非常多
00:19
about the far reaches of the universe,
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关于浩瀚宇宙的深奥知识。
00:22
which is at the same time tremendously important
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与此同时，宇宙是又是极为的重要
00:26
and extremely remote,
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并且极为的遥远，
00:28
and yet much, much closer,
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然而同时，它又比很多我们并不明白的事物
00:30
much more directly related to us,
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离我们更近，
00:32
there are many things we don't really understand.
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跟我们更加直接相关。
00:35
And one of them is the extraordinary
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我们不明白的事情之一
00:37
social complexity of the animals around us,
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就是我们周围这些动物的社会复合性。
00:40
and today I want to tell you a few stories
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今天我想给你们讲几个
00:42
of animal complexity.
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关于动物的复合性的故事。
00:44
But first, what do we call complexity?
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首先，什么被我们称为复合性呢？
00:48
What is complex?
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复合是什么？
00:49
Well, complex is not complicated.
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复合并不是复杂。
00:53
Something complicated comprises many small parts,
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一件复杂的事物是由很多小部分所组成的，
00:56
all different, and each of them
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每一部分都各不相同，而且每一部分都
00:58
has its own precise role in the machinery.
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在这个体系中有其自身的确切作用。
01:02
On the opposite, a complex system
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与之相反，（这是）一个复合的系统
01:04
is made of many, many similar parts,
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由很多很多类似的部件所组成，
01:07
and it is their interaction
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而且（就是因为）他们之间的相互影响
01:09
that produces a globally coherent behavior.
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才形成了一种宏观上一致的行为。
01:12
Complex systems have many interacting parts
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复合系统含有很多相互动的的元素，
01:16
which behave according to simple, individual rules,
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它们根据简单的、 个体的规则行动，
01:20
and this results in emergent properties.
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这（样)就导致了（新的）特征的出现。
01:23
The behavior of the system as a whole
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系统作为一个整体的行为
01:25
cannot be predicted
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是无法仅仅根据
01:26
from the individual rules only.
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个体规则推测出来的。
01:29
As Aristotle wrote,
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正如亚里斯多德写道：
01:30
the whole is greater than the sum of its parts.
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整体大于其各部分的总和。
01:33
But from Aristotle, let's move onto
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但是让我们从亚里斯多德转到
01:36
a more concrete example of complex systems.
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复杂系统的一个更具体的例子吧。
01:40
These are Scottish terriers.
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这里有几条苏格兰梗犬。
01:42
In the beginning, the system is disorganized.
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开始时，该系统是混乱无章的。
01:45
Then comes a perturbation: milk.
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现在来点干扰： 牛奶。
01:49
Every individual starts pushing in one direction
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每个个体开始向同一个方向推动，
01:53
and this is what happens.
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然后就会变成这样。
01:56
The pinwheel is an emergent property
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风车式的运动是一个新出现的特征，
01:59
of the interactions between puppies
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它源于小狗们之间的相互作用（配合）
02:01
whose only rule is to try to keep access to the milk
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小狗们唯一的规则就是要尽量够得着牛奶
02:05
and therefore to push in a random direction.
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因此它们就向一个随机的方向推。
02:09
So it's all about finding the simple rules
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所以就是要找到
02:13
from which complexity emerges.
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从简单规则中突现出的复合性。
02:15
I call this simplifying complexity,
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我把这称之为简化复杂性，
02:18
and it's what we do at the chair of systems design
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这就是我们在苏黎世ETH系统设计院
02:20
at ETH Zurich.
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所做的事。
02:22
We collect data on animal populations,
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我们收集关于动物族群的数据，
02:26
analyze complex patterns, try to explain them.
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分析复合模式，尝试解释它们。
02:30
It requires physicists who work with biologists,
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这需要物理学家与生物学家，
02:32
with mathematicians and computer scientists,
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还有数学家和计算机科学家共同合作，
02:35
and it is their interaction that produces
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并且这是他们的相互动所产生出的
02:38
cross-boundary competence
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交叉（跨学科）式的能力
02:40
to solve these problems.
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可以用来解决这些问题。
02:41
So again, the whole is greater
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再一次，这样一来整体是
02:44
than the sum of the parts.
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比各个部分的总和要大。
02:45
In a way, collaboration
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从某种程度上说，合作
02:47
is another example of a complex system.
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是复合系统的另一个例子。
02:51
And you may be asking yourself
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你可能会问自己，
02:52
which side I'm on, biology or physics?
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我是在哪一个（学科的分支）上面呢，生物学家还是物理学家呢？
02:55
In fact, it's a little different,
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事实上，都不是，
02:57
and to explain, I need to tell you
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要解释这一点，我得告诉你
02:59
a short story about myself.
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关于我自己的一个小故事。
03:01
When I was a child,
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当我还是个孩子的时候，
03:03
I loved to build stuff, to
create complicated machines.
create complicated machines.
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我喜欢打造东西，创建复杂的机器。
03:07
So I set out to study electrical engineering
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所以我决定去学电气工程
03:10
and robotics,
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和机器人(技术)。
03:11
and my end-of-studies project
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我的结业项目
03:14
was about building a robot called ER-1 --
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是造一个名叫 ER-1的机器人，
03:16
it looked like this—
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看起来就像这样—
03:18
that would collect information from its environment
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它可以从其环境中收集信息，
03:21
and proceed to follow a white line on the ground.
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然后沿着地面上的白线前进。
03:24
It was very, very complicated,
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这个机器人非常、 非常复杂，
03:27
but it worked beautifully in our test room,
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但它在我们的测试室特别好使。
03:30
and on demo day, professors had
assembled to grade the project.
assembled to grade the project.
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到了演示的那天，教授们聚集在一起要给我们的项目打分。
03:33
So we took ER-1 to the evaluation room.
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于是我们把ER1带到评估室。
03:36
It turned out, the light in that room
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结果，那间房间里的灯光
03:38
was slightly different.
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稍有不同，
03:40
The robot's vision system got confused.
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(这样一来)机器人的视觉系统就被弄糊涂了。
03:42
At the first bend in the line,
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在白线第一个转弯的地方，
03:44
it left its course, and crashed into a wall.
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它就偏离了路线，然后撞到了墙上。
03:48
We had spent weeks building it,
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我们花了好几个星期来打造它，
03:50
and all it took to destroy it
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结果使它毁于一旦的
03:52
was a subtle change in the color of the light
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(竟然只)是房间里灯光颜色的
03:54
in the room.
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微妙的变化。
03:56
That's when I realized that
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这使我意识到，
03:57
the more complicated you make a machine,
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你把一台机器造得越复杂，
04:00
the more likely that it will fail
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它就越有可能会由于
04:02
due to something absolutely unexpected.
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某个绝对意想到不的因素而失败。
04:04
And I decided that, in fact,
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于是我决定，其实，
04:06
I didn't really want to create complicated stuff.
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我并不想创建复杂的东西。
04:09
I wanted to understand complexity,
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我想要了解的是复合性，
04:12
the complexity of the world around us
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我们周围的世界的复合性，
04:14
and especially in the animal kingdom.
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尤其是在动物王国里。
04:17
Which brings us to bats.
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这就得说到蝙蝠。
04:20
Bechstein's bats are a common
species of European bats.
species of European bats.
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彼氏鼠耳蝠是一种常见的欧洲蝙蝠。
04:23
They are very social animals.
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他们是非常具有社会性的动物。
04:24
Mostly they roost, or sleep, together.
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通常他们栖息或睡在一起，
04:28
And they live in maternity colonies,
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而且他们生活在母系的群落里。
04:29
which means that every spring,
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这就意味着每年春天，
04:31
the females meet after the winter hibernation,
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雌蝙蝠在冬眠后聚在一起，
04:34
and they stay together for about six months
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然后一起生活大约六个月
04:36
to rear their young,
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来养育后代。
04:39
and they all carry a very small chip,
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他们身上都携带了很小的芯片，
04:42
which means that every time one of them
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这样每次他们其中之一
04:43
enters one of these specially equipped bat boxes,
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进入一个这种具有特殊装备的蝙蝠盒，
04:46
we know where she is,
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我们就知道她在哪里
04:48
and more importantly,
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更重要的是，
04:49
we know with whom she is.
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我们知道她和谁在一起。
04:52
So I study roosting associations in bats,
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所以我研究的是蝙蝠的栖息联系，
04:56
and this is what it looks like.
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看起来就像这样：
04:58
During the day, the bats roost
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白天的时候，蝙蝠
05:00
in a number of sub-groups in different boxes.
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分成很多小组栖息在不同的蝙蝠盒里。
05:03
It could be that on one day,
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有可能某一天，
05:05
the colony is split between two boxes,
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整个群落分在两个盒子里，
05:07
but on another day,
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但是另一天，
05:08
it could be together in a single box,
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它们可能一起聚在一个盒子里，
05:10
or split between three or more boxes,
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或者分到三个或或更多个盒子里，
05:13
and that all seems rather erratic, really.
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这一切看起来确实相当混乱。
05:16
It's called fission-fusion dynamics,
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这被称为裂变融合动态，
05:19
the property for an animal group
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指一群动物
05:21
of regularly splitting and merging
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定期拆分和合并
05:23
into different subgroups.
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到不同的子组里的特性。
05:24
So what we do is take all these data
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所以我们做的是收集来自不同的天
05:27
from all these different days
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所有这些数据
05:29
and pool them together
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并把它们集中在一起
05:30
to extract a long-term association pattern
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来提取一个长期的关联模式。
05:33
by applying techniques with network analysis
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通过应用技术与网络分析，
05:35
to get a complete picture
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我们可以获得一份
05:37
of the social structure of the colony.
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关于整个群落社会结构的完整图片。
05:39
Okay? So that's what this picture looks like.
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对吧？这张图片看起来是这样子。
05:44
In this network, all the circles
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在这个网络中，所有的圈
05:46
are nodes, individual bats,
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是节点，是蝙蝠个体，
05:49
and the lines between them
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而它们之间的连线
05:50
are social bonds, associations between individuals.
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是社会纽带，是个体之间的关联。
05:54
It turns out this is a very interesting picture.
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事实证明这是张非常有趣的图片。
05:57
This bat colony is organized
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整个蝙蝠群
05:59
in two different communities
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被分成两个不同的社区，
06:01
which cannot be predicted
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这是无法
06:02
from the daily fission-fusion dynamics.
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从日常的裂变未来动态中预测出来的。
06:05
We call them cryptic social units.
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我们把他们称为隐性社会单位。
06:08
Even more interesting, in fact:
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更有趣的是
06:10
Every year, around October,
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每年10月前后
06:12
the colony splits up,
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种群分散开了
06:14
and all bats hibernate separately,
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所有蝙蝠都分开冬眠，
06:17
but year after year,
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但是年复一年，
06:18
when the bats come together again in the spring,
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当蝙蝠在春天再一次聚在一起的时候，
06:21
the communities stay the same.
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两个群体保持不变。
06:24
So these bats remember their friends
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所以这些蝙蝠可以记住他们的朋友
06:26
for a really long time.
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并且记住很长时间。
06:28
With a brain the size of a peanut,
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(虽然)大脑只有花生粒大小，
06:31
they maintain individualized,
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他们却保持个性化、
06:33
long-term social bonds,
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长期的社会纽带，
06:35
We didn't know that was possible.
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在此之前我们不知道这是有可能的。
06:37
We knew that primates
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我们知道灵长类动物，
06:38
and elephants and dolphins could do that,
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还有大象和海豚能做到这一点，
06:41
but compared to bats, they have huge brains.
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但与蝙蝠相比，他们有巨大的大脑。
06:44
So how could it be
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所以（蝙蝠的大脑）怎么可能
06:46
that the bats maintain this complex,
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让蝙蝠们保持这个复合的、
06:48
stable social structure
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稳定的社会结构，
06:50
with such limited cognitive abilities?
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而又（只有）在如此有限的认知能力（的情况下）呢？
06:53
And this is where complexity brings an answer.
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在这里复合性就给予了一个解答
06:56
To understand this system,
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要了解这个系统，
06:58
we built a computer model of roosting,
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我们建立了一个栖息的计算机模型。
07:01
based on simple, individual rules,
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基于简单的、 个体的规则，
07:03
and simulated thousands and thousands of days
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然后虚拟的蝙蝠群里模拟
07:05
in the virtual bat colony.
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成千上万的日子。
07:07
It's a mathematical model,
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这是一个数学模型，
07:10
but it's not complicated.
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但它并不复杂。
07:12
What the model told us is that, in a nutshell,
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简而言之，该模型告诉我们的是，
07:15
each bat knows a few other colony members
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每个蝙蝠认识种群少数的其他几个成员，
07:18
as her friends, and is just slightly more likely
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把她们当作朋友，而且只是稍微更有可能
07:20
to roost in a box with them.
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在与他们栖息在同一个盒子里。
07:23
Simple, individual rules.
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简单的、 个体的规则。
07:25
This is all it takes to explain
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这些就足以解释
07:27
the social complexity of these bats.
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这些蝙蝠的社会复合性。
07:29
But it gets better.
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还有更有趣的呢。
07:31
Between 2010 and 2011,
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2010 年和 2011 年之间，
07:34
the colony lost more than two thirds of its members,
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种群失去了三分之二的成员，
07:37
probably due to the very cold winter.
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可能因为那年寒冷的冬天。
07:40
The next spring, it didn't form two communities
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第二年春天，没有像每年那样
07:44
like every year,
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形成两个社群，
07:45
which may have led the whole colony to die
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那样就可能会导致整个种群的死亡，
07:47
because it had become too small.
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因为它变得太小了。
07:49
Instead, it formed a single, cohesive social unit,
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取而代之的是，它形成了一个单一、 紧密的社会单位，
07:54
which allowed the colony to survive that season
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这就使种群在那一季度中幸存了下来，
07:57
and thrive again in the next two years.
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并在随后的两年里再次蓬勃发展。
08:00
What we know is that the bats
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我们知道那些蝙蝠
08:02
are not aware that their colony is doing this.
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并不知道他们的种群在这样做。
08:05
All they do is follow simple association rules,
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所有他们所做的只是去遵循简单的关联规则，
08:09
and from this simplicity
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而从这简单性（中），
08:10
emerges social complexity
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涌现出了社会复合性
08:12
which allows the colony to be resilient
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（这种社会复合型又）使得种群重新振作，
08:15
against dramatic changes
in the population structure.
in the population structure.
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（同时）去抵抗群体结构的巨大变化。
08:18
And I find this incredible.
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我觉得这令人难以置信。
08:21
Now I want to tell you another story,
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现在我想告诉你另一个故事，
08:23
but for this we have to travel from Europe
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但（为了这个故事）我们必须从欧洲
08:24
to the Kalahari Desert in South Africa.
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到南非的卡拉哈里沙漠去。
08:28
This is where meerkats live.
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猫鼬就住在那里。
08:30
I'm sure you know meerkats.
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我确信你们知道猫鼬。
08:31
They're fascinating creatures.
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他们是很有趣的生物。
08:33
They live in groups with a
very strict social hierarchy.
very strict social hierarchy.
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他们生活在具有非常严格的社会等级制度的群体里。
08:36
There is one dominant pair,
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群体里有一对地位最高，
08:38
and many subordinates,
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还有很多下属，
08:39
some acting as sentinels,
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有的充当哨兵，
08:41
some acting as babysitters,
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有的充当保姆，
08:42
some teaching pups, and so on.
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还有的教习幼仔，等等。
08:44
What we do is put very small GPS collars
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我们所做的就是把很小的 GPS 项圈
08:47
on these animals
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放在这些动物身上
08:49
to study how they move together,
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来研究他们是如何一起行动的，
08:51
and what this has to do with their social structure.
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同时（研究）这与它们的社会结构有什么关系。
08:54
And there's a very interesting example
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这里有一个非常有趣的例子
08:56
of collective movement in meerkats.
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关于猫鼬的集体活动行为
08:59
In the middle of the reserve which they live in
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在它们居住的保护区的中央
09:01
lies a road.
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有一条马路。
09:02
On this road there are cars, so it's dangerous.
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这条路上有车，所以是很危险的。
09:05
But the meerkats have to cross it
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但猫鼬们必须穿过去，
09:08
to get from one feeding place to another.
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才能从一个猎食地到达下一个。
09:10
So we asked, how exactly do they do this?
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所以我们就问，他们到底是怎么做到的呢？
09:15
We found that the dominant female
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我们发现，地位最高的雌猫鼬，
09:17
is mostly the one who leads the group to the road,
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多数时候（都）是她领着整个群体来到马路边，
09:19
but when it comes to crossing it, crossing the road,
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但是到要横穿马路的时候，
09:23
she gives way to the subordinates,
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她就让路给她的下属，
09:25
a manner of saying,
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（好像）用这种方式在说，
09:27
"Go ahead, tell me if it's safe."
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“ 去吧，告诉我是不是安全。”
09:30
What I didn't know, in fact,
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事实上我不知道的是，
09:31
was what rules in their behavior the meerkats follow
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这些猫鼬遵循了什么样的行为规则，
09:34
for this change at the edge of the group to happen
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可以使群体的边缘发生这样的变化，
09:37
and if simple rules were sufficient to explain it.
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而且，是否用简单的规则就足以解释它。
09:41
So I built a model, a model of simulated meerkats
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因此我建了一个模型，一个模拟猫鼬
09:45
crossing a simulated road.
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横穿一条模拟马路的模型。
09:47
It's a simplistic model.
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这是一个非常简化的模型。
09:49
Moving meerkats are like random particles
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正在移动的猫鼬就像随机质点一样
09:52
whose unique rule is one of alignment.
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其唯一的规则就是排成一列。
09:54
They simply move together.
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他们只是一起行动。
09:56
When these particles get to the road,
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当这些粒子到达马路时，
10:00
they sense some kind of obstacle,
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他们感觉到某种障碍，
10:01
and they bounce against it.
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然后他们撞了上去。
10:04
The only difference
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那只地位最高的雌猫鼬，
10:05
between the dominant female, here in red,
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这里红色的这只，
10:07
and the other individuals,
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和其他个体的唯一差别，
10:08
is that for her, the height of the obstacle,
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就是对她来说障碍物的高度，
10:11
which is in fact the risk perceived from the road,
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实际上就是被察觉的马路上的风险，
10:13
is just slightly higher,
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稍稍高了一点儿。
10:15
and this tiny difference
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这个个体运动规则中的
10:17
in the individual's rule of movement
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小小的区别
10:19
is sufficient to explain what we observe,
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足以解释我们所观察到的现象，
10:21
that the dominant female
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也就是地位最高的雌猫鼬，
10:24
leads her group to the road
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领着她的群体到马路边，
10:25
and then gives way to the others
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然后让路给其他猫鼬，
10:27
for them to cross first.
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让它们先过马路。
10:30
George Box, who was an English statistician,
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乔治·鲍克斯，他是一个英国的统计学家，
10:33
once wrote, "All models are false,
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曾经写道，“所有的模型是虚构的，
10:36
but some models are useful."
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但有些模型是有用的。”
10:38
And in fact, this model is obviously false,
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事实上，这个模型显然是假的，
10:42
because in reality, meerkats are
anything but random particles.
anything but random particles.
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因为在现实中，猫鼬决不是什么随机粒子。
10:46
But it's also useful,
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但是这个模型也挺有用的，
10:47
because it tells us that extreme simplicity
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因为它告诉我们这种极端简单，
10:50
in movement rules at the individual level
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在个体层面的运动规则，
10:53
can result in a great deal of complexity
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到了群体的层面上，
10:56
at the level of the group.
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就可以导致很大的复合性。
10:58
So again, that's simplifying complexity.
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再说一次，这就是简化复合性。
11:02
I would like to conclude
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最后我要说的是
11:03
on what this means for the whole species.
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这对整个物种意味着什么。
11:06
When the dominant female
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当地位最高的雌猫鼬
11:08
gives way to a subordinate,
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给下属让路，
11:09
it's not out of courtesy.
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它不是出于礼貌。
11:11
In fact, the dominant female
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事实上，地位最高的雌猫鼬
11:13
is extremely important for the cohesion of the group.
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对这个群体的凝聚力来说非常重要。
11:15
If she dies on the road, the whole group is at risk.
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如果她死在马路上，整个集团将处于危险之中。
11:19
So this behavior of risk avoidance
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所以这种风险规避的行为
11:21
is a very old evolutionary response.
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是一个非常古老的进化反应。
11:24
These meerkats are replicating an evolved tactic
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这些猫鼬只是在重复一个已经进化好的策略。
11:28
that is thousands of generations old,
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这个策略已经历经成千上万代了，
11:30
and they're adapting it to a modern risk,
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现在他们在把它向（抵抗）现代风险做改进，
11:32
in this case a road built by humans.
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在这里（现代风险）是人类所建的一条路。
11:36
They adapt very simple rules,
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他们改进非常简单的规则，
11:38
and the resulting complex behavior
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而由此产生的复合行为
11:40
allows them to resist human encroachment
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使它们可以抵抗人类
11:43
into their natural habitat.
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对于它们的自然栖息的入侵。
11:46
In the end,
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最后，
11:48
it may be bats which change their social structure
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这也许是蝙蝠通过改变它们的社会结构
11:50
in response to a population crash,
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去应对群体的灾难；
11:53
or it may be meerkats
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也许是猫鼬
11:54
who show a novel adaptation to a human road,
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对人造的马路所表现出新型的适应方式的
11:57
or it may be another species.
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或者也可能是另一个物种。
12:00
My message here -- and it's not a complicated one,
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我这里（想要传达的）信息不是一个复杂的问题，
12:03
but a simple one of wonder and hope --
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而是一个简单惊叹与希望
12:06
my message here is that animals
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我（要传达）的信息时是，动物
12:09
show extraordinary social complexity,
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显示出非同寻常的社会复合性，
12:11
and this allows them to adapt
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这允许他们能够适应
12:13
and respond to changes in their environment.
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并对他们的环境的变化作出响应。
12:17
In three words, in the animal kingdom,
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用三个字来说就是，在动物王国中，
12:20
simplicity leads to complexity
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简单性导致复合性，
12:22
which leads to resilience.
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复合性又导致适应力。
12:24
Thank you.
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谢谢。
12:26
(Applause)
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（掌声）
12:42
Dania Gerhardt: Thank you very much, Nicolas,
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达尼亚格哈特：尼古拉斯，非常感谢你
12:44
for this great start. Little bit nervous?
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带来这么好的一个开场。 有点紧张么？
12:47
Nicolas Perony: I'm okay, thanks.
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尼古拉斯普莱尼：我还好，谢谢。
12:49
DG: Okay, great. I'm sure a
lot of people in the audience
lot of people in the audience
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达尼亚格哈特：好的，很好。我确信观众席中的许多人
12:52
somehow tried to make associations
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以某种方式试图去在你谈论的动物比如蝙蝠和猫鼬
12:53
between the animals you were talking about --
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与人之间
12:55
the bats, meerkats -- and humans.
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建立关联
12:57
You brought some examples:
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你带来了几个例子
12:58
The females are the social ones,
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雌性们是上流社会中的个体
13:00
the females are the dominant ones,
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雌性们（还是）有统治地位的个体
13:02
I'm not sure who thinks how.
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我不确定谁会去思考为什么（会这样）。
13:04
But is it okay to do these associations?
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但是，（在人与动物之间）做这样的关联妥当么？
13:06
Are there stereotypes you can confirm in this regard
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有没有（一些）在这方面你可以确定的模式化见解
13:09
that can be valid across all species?
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是否这样的一个关联在所有的物种之间都是可行的呢？
13:13
NP: Well, I would say there are also
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尼古拉斯普莱尼： 我想说，确实也有
13:14
counter-examples to these stereotypes.
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对于这些模式化见解的反例。
13:16
For examples, in sea horses or in koalas, in fact,
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举个例子，在海马或者考拉之中，其实，
13:19
it is the males who take care of the young always.
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总是由雄性来照顾他们的幼仔的。
13:23
And the lesson is that it's often difficult,
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（我们所学到的）经验教训是，有时这是有些困难
13:28
and sometimes even a bit dangerous,
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并且时常有一点危险
13:30
to draw parallels between humans and animals.
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在人类与动物之间进行对比。
13:32
So that's it.
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这也就是我的回答了。
13:35
DG: Okay. Thank you very much for this great start.
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达尼亚格哈特：好的。感谢你如此精彩的开场。
13:37
Thank you, Nicolas Perony.
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尼古拉斯普莱尼，谢谢你。
ABOUT THE SPEAKER
Nicolas Perony - Animal scientistNicolas Perony models the movement of animal groups to understand: what is the individual behavior that guides the behavior of the larger society?
Why you should listen
Nicolas Perony started his career as a roboticist. But after one of his robots -- which was designed to follow a white line -- destroyed itself because of a lighting snafu on demo day, he realized that he was less interested in creating complicated robots and more interested in studying the complexity that already exists out there in the animal kingdom. He quickly changed course and is now a quantitative scientist at the Chair of Systems Design at ETH Zurich, where he studies the structure and dynamics of animal societies.
Perony conducts his research by placing GPS collars on animals like Bechstein's bats and meerkats, and studying the spacial data of the group. He creates models of the movement over time to see patterns. He then tries to ascertain at the simple rules that individuals in the animal group seem to be following that, when done en masse, result in the larger flow. In other words, he looks at the underlying mechanics that lead to the collective movement of animal groups.
Nicolas Perony | Speaker | TED.com