ABOUT THE SPEAKER
Deborah Gordon - Ecologist
By studying how ant colonies work without any one leader, Deborah Gordon has identified striking similarities in how ant colonies, brains, cells and computer networks regulate themselves.

Why you should listen

Ecologist Deborah M. Gordon has learned that ant colonies can work without central control by using simple interactions like how often the insects touch antennae. Contrary to the notion that colonies are organized by efficient ants, she has instead discovered that evolution has produced “noisy” systems that tolerate accident and respond flexibly to the environment. When conditions are tough, natural selection favors colonies that conserve resources.

Her studies of ant colonies have led her and her Stanford colleagues to the discovery of the “Anternet,” which regulates foraging in ants in the same way the internet regulates data traffic. But as she said to Wired in 2013, "Insect behavior mimicking human networks ... is actually not what’s most interesting about ant networks. What’s far more interesting are the parallels in the other direction: What have the ants worked out that we humans haven’t thought of yet?" Her latest exploration: How do ants behave in space?

More profile about the speaker
Deborah Gordon | Speaker | TED.com
TED2014

Deborah Gordon: What ants teach us about the brain, cancer and the Internet

蚂蚁在脑科学、癌症和互联网领域带给我们的启发

Filmed:
1,481,089 views

只要在有蚂蚁的地方,生态学者黛博拉·高登都会去研究它们-沙漠,热带雨林,甚至她的厨房。。。在这个吸引人的谈论中,高登解释了她对于这种大部分人不假思索就赶走的昆虫的热爱。她用实例证明了蚂蚁的生活可以提供一个有用的模型, 帮助包括疾病、(网络)技术和脑科学在内的研究。
- Ecologist
By studying how ant colonies work without any one leader, Deborah Gordon has identified striking similarities in how ant colonies, brains, cells and computer networks regulate themselves. Full bio

Double-click the English transcript below to play the video.

00:13
I study研究 ants蚂蚁
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我研究各种蚂蚁
00:14
in the desert沙漠, in the tropical热带 forest森林
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沙漠中的、热带雨林里的、
00:18
and in my kitchen厨房,
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我厨房里的蚂蚁,
00:19
and in the hills丘陵 around Silicon Valley where I live生活.
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以及我硅谷的家周边山上的蚂蚁。
00:23
I've recently最近 realized实现 that ants蚂蚁
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最近我注意到
00:25
are using运用 interactions互动 differently不同
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蚂蚁在不同的环境下
00:27
in different不同 environments环境,
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交互方式也是不同的,
00:29
and that got me thinking思维
that we could learn学习 from this
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这让我想到或许我们能从中学到些什么
00:31
about other systems系统,
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用到其它系统上。
00:32
like brains大脑 and data数据 networks网络 that we engineer工程师,
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例如大脑结构或者我们的数据网络
00:38
and even cancer癌症.
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甚至是癌症。
00:41
So what all these systems系统 have in common共同
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这些系统的共同点在于
00:43
is that there's no central中央 control控制.
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没有一个中央控制结构。
00:45
An ant蚂蚁 colony殖民地 consists of sterile无菌 female workers工人 --
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蚁群的工蚁由不育的雌性构成—
00:49
those are the ants蚂蚁 you see walking步行 around —
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工蚁就是你能看到的蚂蚁—
00:52
and then one or more reproductive生殖 females女性
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而能够生育的雌性蚂蚁(蚁后)
00:54
who just lay铺设 the eggs.
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只负责产卵。
00:56
They don't give any instructions说明.
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蚁后不会发号指令。
00:58
Even though虽然 they're called queens皇后,
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虽然它们叫做蚁后,
01:00
they don't tell anybody任何人 what to do.
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但是它们不会指挥其它工蚁。
01:02
So in an ant蚂蚁 colony殖民地, there's no one in charge收费,
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所以任何蚁群都没有一个最高负责人,
01:05
and all systems系统 like this without central中央 control控制
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所有这些系统都是没有中央控制的,
01:08
are regulated调控 using运用 very simple简单 interactions互动.
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仅仅通过简单的交互方式进行运作.
01:12
Ants蚂蚁 interact相互作用 using运用 smell.
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蚂蚁的交互是通过嗅觉进行的.
01:15
They smell with their antennae天线,
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它们用触角(antennae)去嗅.
用触角来交流。
01:17
and they interact相互作用 with their antennae天线,
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01:20
so when one ant蚂蚁 touches触摸 another另一个 with its antennae天线,
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所以当一只蚂蚁的触角碰到另一只蚂蚁的触角
01:23
it can tell, for example, if the other ant蚂蚁
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它就知道另一个蚂蚁
01:24
is a nestmatenestmate
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是不是同一个巢穴的
01:26
and what task任务 that other ant蚂蚁 has been doing.
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以及这只蚂蚁正要做什么事情.
01:30
So here you see a lot of ants蚂蚁 moving移动 around
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现在你看到的这个蚂蚁的活动场所
01:33
and interacting互动 in a lab实验室 arena竞技场
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通过玻璃管子跟另外两个场所连接着
01:35
that's connected连接的 by tubes to two other arenas竞技场.
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蚂蚁在这些活动场所里走来走去.
01:39
So when one ant蚂蚁 meets符合 another另一个,
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当一只蚂蚁遇到了另外一支蚂蚁,
01:41
it doesn't matter which哪一个 ant蚂蚁 it meets符合,
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遇见的是哪只蚂蚁并不重要,
01:43
and they're actually其实 not transmitting发射
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它们也没通过触角传递
01:45
any kind of complicated复杂 signal信号 or message信息.
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任何复杂的信号或消息.
01:49
All that matters事项 to the ant蚂蚁 is the rate
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唯一传递的是两只蚂蚁
01:51
at which哪一个 it meets符合 other ants蚂蚁.
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相互遇见的频率.
01:54
And all of these interactions互动, taken采取 together一起,
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这些交互信息汇总起来后,
01:56
produce生产 a network网络.
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我们就得到了一个网络.
01:59
So this is the network网络 of the ants蚂蚁
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这就是刚才你看到的蚂蚁
02:01
that you just saw moving移动 around in the arena竞技场,
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四处移动之后生成的网络图,
02:04
and it's this constantly经常 shifting network网络
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正是这张不断变化中的网络,
02:07
that produces产生 the behavior行为 of the colony殖民地,
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塑造了这个蚁群的行为,
02:10
like whether是否 all the ants蚂蚁 are hiding inside the nest,
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像是有多少蚂蚁躲在巢穴里,
02:12
or how many许多 are going out to forage饲料.
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多少蚂蚁出去寻食之类的信息.
02:15
A brain actually其实 works作品 in the same相同 way,
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大脑差不多也是这么工作的,
02:17
but what's great about ants蚂蚁 is
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相比起来观察蚂蚁吸引人的地方之一,
02:18
that you can see the whole整个 network网络 as it happens发生.
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是你可以看到整个网路是如何运作的.
02:23
There are more than 12,000 species种类 of ants蚂蚁,
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蚂蚁的种类超过一万两千种,
02:26
in every一切 conceivable可以想象 environment环境,
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你能想象到的环境里都有蚂蚁存在,
02:29
and they're using运用 interactions互动 differently不同
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而且不同环境下的蚁群会使用
02:31
to meet遇到 different不同 environmental环境的 challenges挑战.
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不同的交流方式以适应环境特点.
02:34
So one important重要 environmental环境的 challenge挑战
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例如不同环境下不同蚁群
02:36
that every一切 system系统 has to deal合同 with
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普遍面临的问题之一
02:38
is operating操作 costs成本, just what it takes
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是如何控制"运营开支", 即需要花多大成本
02:40
to run the system系统.
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才能生存下来.
02:42
And another另一个 environmental环境的 challenge挑战 is resources资源,
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另一个环境带来的挑战是,
02:45
finding发现 them and collecting搜集 them.
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如何去搜寻和收集资源.
02:47
In the desert沙漠, operating操作 costs成本 are high
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在沙漠中, 水非常的稀少,
02:50
because water is scarce稀缺,
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所以运营开支很大,
02:52
and the seed-eating种子为食 ants蚂蚁 that I study研究 in the desert沙漠
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我研究的一种生活在沙漠中以植物种子为食的蚂蚁
02:54
have to spend water to get water.
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寻找水源的同时需要消耗水.
02:57
So an ant蚂蚁 outside foraging觅食,
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所以当一只蚂蚁外出觅食的时候,
02:59
searching搜索 for seeds种子 in the hot sun太阳,
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在火辣辣的太阳底下找种子的时候,
03:01
just loses失去 water into the air空气.
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它体内的水分会被蒸发.
03:03
But the colony殖民地 gets得到 its water
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而蚁群
03:05
by metabolizing代谢 the fats脂肪 out of the seeds种子
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可以通过消化种子富含的脂肪
03:07
that they eat.
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产生需要的水.
03:09
So in this environment环境, interactions互动 are used
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所以在这种环境下, 蚂蚁之间的交互
03:12
to activate启用 foraging觅食.
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主要用来决定是否外出觅食.
03:14
An outgoing传出 forager觅食 doesn't go out unless除非
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一个准备外出的觅食者不会轻易外出,
03:16
it gets得到 enough足够 interactions互动 with returning回国 foragers征粮,
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除非得到了足够的归巢的觅食者的反馈,
03:18
and what you see are the returning回国 foragers征粮
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你现在看到的是回来的觅食者,
03:20
going into the tunnel隧道, into the nest,
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在通过蚁巢的管道进入蚁穴时,
03:22
and meeting会议 outgoing传出 foragers征粮 on their way out.
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跟沿路准备外外出的蚂蚁进行交流.
03:25
This makes品牌 sense for the ant蚂蚁 colony殖民地,
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这对蚁群来说很重要,
03:26
because the more food餐饮 there is out there,
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因为外面的食物越多,
03:29
the more quickly很快 the foragers征粮 find it,
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觅食的蚂蚁找到食物的速度越快,
03:31
the faster更快 they come back,
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它们回来的就更快,
03:32
and the more foragers征粮 they send发送 out.
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那么就会有更多的蚂蚁出去觅食.
03:35
The system系统 works作品 to stay stopped停止,
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这个系统默认的行为是按兵不动,
03:37
unless除非 something positive happens发生.
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除非看到了足够的好处.
03:39
So interactions互动 function功能 to activate启用 foragers征粮.
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所以在这里交互是为了决定是否出去觅食.
03:43
And we've我们已经 been studying研究
the evolution演化 of this system系统.
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我们已经研究这种系统演化有一段时间了.
03:46
First of all, there's variation变异.
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首先, 这种演化各不相同.
03:47
It turns out that colonies群落 are different不同.
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不同的蚁群的行为是不一样的.
03:50
On dry days, some colonies群落 forage饲料 less,
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在旱季, 有些蚁群觅食的少,
03:52
so colonies群落 are different不同 in how
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不同蚁群之间的差异
03:54
they manage管理 this trade-off交易
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就体现在它们如何做权衡
03:55
between之间 spending开支 water to search搜索 for seeds种子
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如何在消耗更多水分去寻找食物
03:58
and getting得到 water back in the form形成 of seeds种子.
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以及获得更多食物和水之间权衡
04:02
And we're trying to understand理解 why
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我们尝试将蚁群
04:03
some colonies群落 forage饲料 less than others其他
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类比成神经细胞组织
04:05
by thinking思维 about ants蚂蚁 as neurons神经元,
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基于脑神经科学的相关理论
04:08
using运用 models楷模 from neuroscience神经科学.
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来理解蚁群觅食行为的差异。
04:10
So just as a neuron神经元 adds增加 up its stimulation促进
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所以就像是一个神经元是否触发,
04:13
from other neurons神经元 to decide决定 whether是否 to fire,
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取决于相连的神经元触发强度之和,
04:15
an ant蚂蚁 adds增加 up its stimulation促进 from other ants蚂蚁
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蚂蚁的行为也由其它蚂蚁决定,
04:18
to decide决定 whether是否 to forage饲料.
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是否要出去觅食。
04:20
And what we're looking for is whether是否 there might威力 be
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于是我们就希望能够找到
04:21
small differences分歧 among其中 colonies群落
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觅食行为存在差异的蚁群之间
04:23
in how many许多 interactions互动 each ant蚂蚁 needs需求
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是否蚂蚁在觅食前交互的其它蚂蚁数量
04:27
before it's willing愿意 to go out and forage饲料,
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也是存在对应差异的。
04:29
because a colony殖民地 like that would forage饲料 less.
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因为像那样的蚁群会更少外出觅食。
04:32
And this raises加薪 an analogous类似 question about brains大脑.
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这个问题也可以用大脑来进行类比。
04:35
We talk about the brain,
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我们提到的大脑
04:37
but of course课程 every一切 brain is slightly different不同,
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当然也是每个大脑都有些许不同的
04:40
and maybe there are some individuals个人
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肯定有一些个体
04:41
or some conditions条件
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在某些环境下
04:42
in which哪一个 the electrical电动 properties性能 of neurons神经元 are such这样
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他们的神经元的电特性决定了
04:46
that they require要求 more stimulus刺激物 to fire,
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需要接受更多的刺激才会激发。
04:50
and that would lead to differences分歧 in brain function功能.
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而这会导致脑的功能差异。
04:53
So in order订购 to ask evolutionary发展的 questions问题,
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而为了解答之前系统演化的问题,
04:56
we need to know about reproductive生殖 success成功.
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我们首先需要研究下后代繁殖率。
04:58
This is a map地图 of the study研究 site现场
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这张图显示的是我的研究站附近的蚁群图
05:01
where I have been tracking追踪 this population人口
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我在这个地方研究收获蚂蚁(一种西方蚁)
05:03
of harvester收割机 ant蚂蚁 colonies群落 for 28 years年份,
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种群演化已经超过28年了。
05:06
which哪一个 is about as long as a colony殖民地 lives生活.
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这大概也是一个种群能够延续的时间。
05:09
Each symbol符号 is a colony殖民地,
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每一个圆圈都表示一个种群,
05:11
and the size尺寸 of the symbol符号 is
how many许多 offspring子孙 it had,
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圆圈的大小表示后代的规模,
05:14
because we were able能够 to use genetic遗传 variation变异
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我们可以通过基因变化分析(genetic variation)
05:16
to match比赛 up parent and offspring子孙 colonies群落,
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来确认种群之间的父子关系,
05:19
that is, to figure数字 out which哪一个 colonies群落
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也就是能够确认每个蚁群
05:22
were founded成立 by a daughter女儿 queen女王
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里面的蚁后来自于
05:24
produced生成 by which哪一个 parent colony殖民地.
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哪个父代蚁群。
05:26
And this was amazing惊人 for me, after all these years年份,
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研究这么多年之后我有了一些
05:28
to find out, for example, that colony殖民地 154,
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迷人的发现,例如,154号种群,
05:31
whom I've known已知 well for many许多 years年份,
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我研究很多年的这个,
05:33
is a great-grandmother曾祖母.
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算是祖母级别的。
05:35
Here's这里的 her daughter女儿 colony殖民地,
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这是她的女儿种群,
05:37
here's这里的 her granddaughter孙女 colony殖民地,
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这是她的孙女种群,
05:40
and these are her great-granddaughter曾孙女 colonies群落.
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这是重孙女种群。
05:42
And by doing this, I was able能够 to learn学习
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分析这些种群使我能够
05:44
that offspring子孙 colonies群落 resemble类似 parent colonies群落
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发现后代种群(的多少)体现了
05:47
in their decisions决定 about which哪一个 days are so hot
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父代种群在炎热天气下
05:49
that they don't forage饲料,
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觅食的策略差异,
05:51
and the offspring子孙 of parent colonies群落
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而且考虑到父代种群
05:53
live生活 so far from each other that the ants蚂蚁 never meet遇到,
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与后代种群之间距离很远,不可能遇见,
05:56
so the ants蚂蚁 of the offspring子孙 colony殖民地
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所以后代种群中的蚂蚁
05:58
can't be learning学习 this from the parent colony殖民地.
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不会从父代种群那里学习到什么。
06:00
And so our next下一个 step is to look
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于是第二步就是看看
06:02
for the genetic遗传 variation变异
underlying底层 this resemblance相似.
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这种相似性的基因学变异根源。
06:07
So then I was able能够 to ask, okay, who's谁是 doing better?
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然后我就可以提出这个问题:哪群蚂蚁的策略更好?
06:11
Over the time of the study研究,
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在研究进行中的那些年里,
06:12
and especially特别 in the past过去 10 years年份,
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尤其是最近的十年,
06:14
there's been a very severe严重 and deepening深化 drought干旱
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实验所在的美国西南部
06:17
in the Southwestern西南 U.S.,
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经历了非常严重和持久的干旱,
06:19
and it turns out that the
colonies群落 that conserve养护 water,
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结果是那些更注重保持水分的蚁群,
06:22
that stay in when it's really hot outside,
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那些大热天不出门的蚁群,
06:27
and thus从而 sacrifice牺牲 getting得到 as much food餐饮 as possible可能,
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也就是那些失去了更多觅食机会的蚁群,
06:29
are the ones那些 more likely容易 to have offspring子孙 colonies群落.
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反而是更有可能有后代蚁群的。
06:32
So all this time, I thought that colony殖民地 154
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我曾经一度认为154号种群
06:35
was a loser失败者, because on really dry days,
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是进化的失败者, 因为在旱季,
06:37
there'd这红色 be just this trickle of foraging觅食,
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它们很少出去觅食,
06:39
while the other colonies群落 were out
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反之其它的种群
06:41
foraging觅食, getting得到 lots of food餐饮,
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会出去寻找更多的食物,
06:43
but in fact事实, colony殖民地 154 is a huge巨大 success成功.
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但是结果是,154号种群非常的成功。
06:46
She's a matriarch女家长.
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她是事实上的统领。
06:47
She's one of the rare罕见 great-grandmothers曾祖母 on the site现场.
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她是这个研究点非常少见的有重孙后代的蚁群
06:50
To my knowledge知识, this is the first time
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就我所知,这还是第一次
06:53
that we've我们已经 been able能够 to track跟踪
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我们人类能够追踪到
06:55
the ongoing不断的 evolution演化 of collective集体 behavior行为
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自然界中野生生物群体的
06:58
in a natural自然 population人口 of animals动物
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集体行为进化
07:00
and find out what's actually其实 working加工 best最好.
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以及找到最适合环境的生存方式.
07:04
Now, the Internet互联网 uses使用 an algorithm算法
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现在, 互联网使用的算法
07:07
to regulate调节 the flow of data数据
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用来分配数据流动的算法
07:10
that's very similar类似 to the one
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与这些蚂蚁使用的算法
07:12
that the harvester收割机 ants蚂蚁 are using运用 to regulate调节
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即如何安排工蚁外出觅食的算法
07:14
the flow of foragers征粮.
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非常相似.
07:16
And guess猜测 what we call this analogy比喻?
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你们猜我们如何称呼这种相似性?
07:19
The anternetanternet is coming未来.
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蚁群互联网(Anternet)的到来.
07:21
(Applause掌声)
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(掌声)
07:23
So data数据 doesn't leave离开 the source资源 computer电脑
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所以发送数据的电脑
07:26
unless除非 it gets得到 a signal信号 that there's enough足够 bandwidth带宽
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在得到信号确认带宽足够之前
07:29
for it to travel旅行 on.
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不会将数据发送出去.
07:32
In the early days of the Internet互联网,
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在互联网的早期,
07:33
when operating操作 costs成本 were really high
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发送和接收数据的成本非常高,
07:35
and it was really important重要 not to lose失去 any data数据,
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所以任何形式的数据丢失都是不可以接受的,
07:38
then the system系统 was set up for interactions互动
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所以网络系统被设计利用相互之间的交互
07:41
to activate启用 the flow of data数据.
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来决定何时发送数据.
07:44
It's interesting有趣 that the ants蚂蚁 are using运用 an algorithm算法
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发现蚂蚁跟我们人类最近才发明的算法
07:46
that's so similar类似 to the one that we recently最近 invented发明,
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有这么大的相似性是很叫人惊喜的,
07:50
but this is only one of a handful少数 of ant蚂蚁 algorithms算法
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而且现在我们只发现了蚂蚁使用的算法中
07:53
that we know about,
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一小部分的算法,
07:54
and ants蚂蚁 have had 130 million百万 years年份
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蚂蚁已经有了1.3亿年的历史
07:58
to evolve发展 a lot of good ones那些,
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已经演化出很多好的算法,
08:00
and I think it's very likely容易
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因此我相信有可能
08:01
that some of the other 12,000 species种类
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另外尚未研究的1.2万蚂蚁种类中
08:04
are going to have interesting有趣 algorithms算法
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也有很多有意思的算法,
08:06
for data数据 networks网络
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可以用于数据网络
08:07
that we haven't没有 even thought of yet然而.
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这些算法甚至超过了我们的想象.
08:10
So what happens发生 when operating操作 costs成本 are low?
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例如, 当运营成本很低的时候呢?
08:13
Operating操作 costs成本 are low in the tropics热带,
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热带雨林里, 蚁群觅食的成本很低,
08:15
because it's very humid湿, and it's easy简单 for the ants蚂蚁
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因为那里非常的湿润, 对于蚁群来说
08:17
to be outside walking步行 around.
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外出觅食也非常容易.
08:20
But the ants蚂蚁 are so abundant丰富
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但是蚂蚁的种类是如此的繁多
08:22
and diverse多种 in the tropics热带
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数量也非常庞大
08:23
that there's a lot of competition竞争.
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因此蚂蚁之间的竞争非常激烈.
08:26
Whatever随你 resource资源 one species种类 is using运用,
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一个蚁群需要用到的任何资源
08:28
another另一个 species种类 is likely容易 to be using运用 that
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基本上都有竞争者
08:31
at the same相同 time.
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与之争夺.
08:33
So in this environment环境, interactions互动 are used
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所以在这样的环境下, 相互接触的用途
08:36
in the opposite对面 way.
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完全反了过来.
08:38
The system系统 keeps保持 going
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蚁群的系统不断的扩张,
08:39
unless除非 something negative happens发生,
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直到一些不好的事情发生,
08:41
and one species种类 that I study研究 makes品牌 circuits电路
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我研究的一种蚁群会在丛林里
08:43
in the trees树木 of foraging觅食 ants蚂蚁
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构建自己的觅食网络,
08:45
going from the nest to a food餐饮 source资源 and back,
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在蚁穴和食物时间不断的来回,
08:48
just round回合 and round回合,
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一圈一圈的觅食,
直到一些不好的事情发生,
08:50
unless除非 something negative happens发生,
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例如遇到了
08:51
like an interaction相互作用
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08:53
with ants蚂蚁 of another另一个 species种类.
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别的种类的蚂蚁.
08:55
So here's这里的 an example of ant蚂蚁 security安全.
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这是蚂蚁安防的一个例子.
08:58
In the middle中间, there's an ant蚂蚁
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中间的位置, 一只蚂蚁
09:00
plugging堵漏 the nest entrance入口 with its head
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在跟另外的种群的蚂蚁触碰了触角之后
09:03
in response响应 to interactions互动 with another另一个 species种类.
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将蚁穴的入口用自己的头挡住了.
09:06
Those are the little ones那些 running赛跑 around
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这些小的、腹部朝上的蚂蚁
09:07
with their abdomens腹部 up in the air空气.
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正在这周围走动.
09:10
But as soon不久 as the threat威胁 is passed通过,
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但是一旦危险解除,
09:12
the entrance入口 is open打开 again,
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入口就会重新开启,
09:15
and maybe there are situations情况
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或许我们也可以联想到
09:17
in computer电脑 security安全
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在计算机安全领域
09:18
where operating操作 costs成本 are low enough足够
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这个领域的运营成本也低到
09:20
that we could just block access访问 temporarily暂时
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我们可以临时的中断网络访问
09:23
in response响应 to an immediate即时 threat威胁,
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以应对临时的威胁,
09:25
and then open打开 it again,
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稍后继续开放,
09:27
instead代替 of trying to build建立
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而不是现在的做法
09:29
a permanent常驻 firewall火墙 or fortress堡垒.
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尝试构造一个永久的防火墙.
09:33
So another另一个 environmental环境的 challenge挑战
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另一个环境带来的挑战
09:35
that all systems系统 have to deal合同 with
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所有的蚁群系统都需要面对的
09:36
is resources资源, finding发现 and collecting搜集 them.
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是如何寻找和搜集资源.
09:42
And to do this, ants蚂蚁 solve解决 the problem问题
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蚁群为了解决这个问题, 采用了
09:44
of collective集体 search搜索,
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集体搜索(collective search)的方法,
09:45
and this is a problem问题 that's of great interest利益
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而这个问题现在已经引起了
09:46
right now in robotics机器人,
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机器人研究人员的极大兴趣,
09:48
because we've我们已经 understood了解 that,
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因为我们都知道,
09:50
rather than sending发出 a single,
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与其用一个单一的
09:51
sophisticated复杂的, expensive昂贵 robot机器人 out
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复杂且昂贵的机器人
09:55
to explore探索 another另一个 planet行星
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去探索另外的星球
09:56
or to search搜索 a burning燃烧 building建造,
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或去火场搜救,
09:59
that instead代替, it may可能 be more effective有效
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或许有更好的方式
10:01
to get a group of cheaper便宜 robots机器人
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就是造一堆便宜的机器人
10:06
exchanging交换 only minimal最小 information信息,
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相互之间仅仅交换简单的信息,
10:08
and that's the way that ants蚂蚁 do it.
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就像是蚂蚁所做的那样.
10:11
So the invasive侵入的 Argentine阿根廷 ant蚂蚁
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这种外来的阿根廷蚂蚁
10:13
makes品牌 expandable扩张 search搜索 networks网络.
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很擅长扩大自己的搜索网络.
10:15
They're good at dealing交易 with the main主要 problem问题
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它们非常善于解决集体搜索中的
10:17
of collective集体 search搜索,
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主要问题,
10:19
which哪一个 is the trade-off交易 between之间
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即如何在两个不同的目标之间权衡
10:21
searching搜索 very thoroughly
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既要能够搜索的彻底
10:23
and covering覆盖 a lot of ground地面.
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又要搜索的范围广.
10:25
And what they do is,
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它们是这么做的,
10:25
when there are many许多 ants蚂蚁 in a small space空间,
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当搜索空间小而蚂蚁很多时,
10:28
then each one can search搜索 very thoroughly
255
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它们会搜寻的非常彻底
10:30
because there will be another另一个 ant蚂蚁 nearby附近
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因为它们知道临近的区域
10:32
searching搜索 over there,
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有别的蚂蚁在搜索,
10:33
but when there are a few少数 ants蚂蚁
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但是当搜索面积很大
10:35
in a large space空间,
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且蚂蚁很少时,
10:37
then they need to stretch伸展 out their paths路径
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它们会扩张自己的搜索路径
10:39
to cover more ground地面.
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去覆盖更大的面积.
10:41
I think they use interactions互动 to assess评估 density密度,
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我想它们之间的接触主要交换的是蚂蚁的密度信息,
10:44
so when they're really crowded,
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当它们的密度很大时,
10:45
they meet遇到 more often经常,
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它们碰见的就越多,
10:46
and they search搜索 more thoroughly.
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搜寻的也就越仔细.
10:49
Different不同 ant蚂蚁 species种类 must必须 use different不同 algorithms算法,
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不同种类的蚂蚁使用的算法应该是不同的,
10:52
because they've他们已经 evolved进化 to deal合同 with
267
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2522
因为随着一代代的演化
10:55
different不同 resources资源,
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它们需要的资源不同.
10:56
and it could be really useful有用 to know about this,
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知道这些差异真的很有用.
10:59
and so we recently最近 asked ants蚂蚁
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所以最近我们把蚂蚁
11:01
to solve解决 the collective集体 search搜索 problem问题
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放在微重力的极端环境中
11:03
in the extreme极端 environment环境
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希望能够帮助
11:04
of microgravity微重力
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国际空间站
11:06
in the International国际 Space空间 Station.
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解决集体搜索的难题.
11:08
When I first saw this picture图片, I thought,
275
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1545
当我第一次看到这张照片, 我想,
11:09
Oh no, they've他们已经 mounted安装 the habitat栖息地 vertically垂直,
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2857
呀, 他们把蚁穴竖起来放着了,
11:12
but then I realized实现 that, of course课程, it doesn't matter.
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2618
但是马上意识到, 其实横竖都一样的.
11:15
So the idea理念 here is that the ants蚂蚁
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这个实验的想法是
11:18
are working加工 so hard to hang on
279
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蚂蚁要花大力气把自己挂在墙上
11:19
to the wall or the floor地板 or whatever随你 you call it
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或者也可以说是地板上, 你怎么看都行
11:23
that they're less likely容易 to interact相互作用,
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这样它们就没有精力去交互了,
11:26
and so the relationship关系 between之间
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所以关于蚂蚁密度的信息
11:27
how crowded they are and how often经常 they meet遇到
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2120
以及它们相互遇见的频率
11:29
would be messed搞砸 up.
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都会乱掉.
11:31
We're still analyzing分析 the data数据.
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我们还在分析这些数据.
11:32
I don't have the results结果 yet然而.
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我还没有结论.
11:34
But it would be interesting有趣 to know
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但如果我们能够知道地球上的
11:36
how other species种类 solve解决 this problem问题
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其它物种如何解决此类问题
11:38
in different不同 environments环境 on Earth地球,
289
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这一定非常的有意思,
11:41
and so we're setting设置 up a program程序
290
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所以我们创建了一个活动
11:42
to encourage鼓励 kids孩子 around the world世界
291
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鼓励全世界的小朋友们
11:44
to try this experiment实验 with different不同 species种类.
292
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2536
用不同的蚂蚁种类重复我们的实验.
11:47
It's very simple简单.
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非常简单.
11:48
It can be doneDONE with cheap低廉 materials物料.
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做起来也不需要多少成本.
11:51
And that way, we could make a global全球 map地图
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这样, 我们就能够绘制一张
11:53
of ant蚂蚁 collective集体 search搜索 algorithms算法.
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蚂蚁集体搜索算法的"世界地图".
11:57
And I think it's pretty漂亮 likely容易 that the invasive侵入的 species种类,
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我想那些外来的蚂蚁种类,
11:59
the ones那些 that come into our buildings房屋,
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那些混进我们大楼的蚂蚁,
12:01
are going to be really good at this,
299
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对于集体搜索非常在行,
12:03
because they're in your kitchen厨房
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因为它们已经跑到你的厨房
12:05
because they're really good
at finding发现 food餐饮 and water.
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非常地善于找到食物和水.
12:09
So the most familiar resource资源 for ants蚂蚁
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对于蚂蚁而言最为相似的资源
12:12
is a picnic野餐,
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是野餐的地方,
12:13
and this is a clustered集群 resource资源.
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是一个集中的资源.
12:16
When there's one piece of fruit水果,
305
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999
当一块水果掉在地上,
12:17
there's likely容易 to be another另一个 piece of fruit水果 nearby附近,
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周围很可能还有更多的水果渣,
12:19
and the ants蚂蚁 that specialize专攻 on clustered集群 resources资源
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因此生活在集中资源多的地方的蚂蚁
12:23
use interactions互动 for recruitment招聘.
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通过相互接触来召集伙伴.
12:24
So when one ant蚂蚁 meets符合 another另一个,
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所以当一只蚂蚁遇见另一只蚂蚁,
12:26
or when it meets符合 a chemical化学 deposited沉积
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或是另一只蚂蚁沿路留下的
12:27
on the ground地面 by another另一个,
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化学气味,
12:29
then it changes变化 direction方向 to follow跟随
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然后它就会改变自己的方向
12:31
in the direction方向 of the interaction相互作用,
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冲着接触方提供的方向去搜寻
12:32
and that's how you get the trail落后 of ants蚂蚁
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这就是为什么能够有一只蚂蚁大军
12:34
sharing分享 your picnic野餐.
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与你分享野餐的原因.
12:36
Now this is a place地点 where I think we might威力 be able能够
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现在, 我觉得我们或许可以
12:38
to learn学习 something from ants蚂蚁 about cancer癌症.
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从蚂蚁身上获得治疗癌症的一些启发.
12:41
I mean, first, it's obvious明显 that we could do a lot
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1981
我是说, 首先, 我们可以做很多事情
12:43
to prevent避免 cancer癌症
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来阻止癌症
12:45
by not allowing允许 people to spread传播 around
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例如禁止有人向其他人销售
12:47
or sell the toxins毒素 that promote促进
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可能增加我们身体患癌症风险的
12:49
the evolution演化 of cancer癌症 in our bodies身体,
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有毒有害商品,
12:52
but I don't think the ants蚂蚁 can help us much with this
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但是我不认为在这点上蚂蚁能够帮助我们什么,
12:55
because ants蚂蚁 never poison their own拥有 colonies群落.
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因为它们从来不会毒害同类.
12:58
But we might威力 be able能够 to learn学习 something from ants蚂蚁
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但是我们或许可以从蚂蚁那里学到一些方法
12:59
about treating治疗 cancer癌症.
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来治疗癌症.
13:01
There are many许多 different不同 kinds of cancer癌症.
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癌症有很多不同的种类.
13:03
Each one originates起源 in a particular特定 part部分 of the body身体,
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每一种癌症一开始都附着在身体的特定部位.
13:06
and then some kinds of cancer癌症 will spread传播
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然后一些类型的癌症(癌细胞)
13:09
or metastasize转移 to particular特定 other tissues组织
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会扩散或传播到其它特定的组织结构中
13:12
where they must必须 be getting得到
resources资源 that they need.
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它们需要在那里获得自己需要的资源.
13:15
So if you think from the perspective透视
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现在如果你从这个角度
13:17
of early metastatic转移性 cancer癌症 cells细胞
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去看待早期癌细胞
13:19
as they're out searching搜索 around
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它们也是在体内搜寻
13:20
for the resources资源 that they need,
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寻找他们需要的资源,
13:23
if those resources资源 are clustered集群,
336
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1983
如果这些资源是集中的,
13:25
they're likely容易 to use interactions互动 for recruitment招聘,
337
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3013
那么它们很可能通过相互接触来召唤更多的癌细胞,
13:28
and if we can figure数字 out how
cancer癌症 cells细胞 are recruiting招聘,
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那么如果我们能够破解癌细胞相互召唤的机制
13:31
then maybe we could set traps陷阱
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我们或许就能够设置陷阱
13:33
to catch抓住 them before they become成为 established既定.
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在癌细胞聚集之前捕获它们.
13:37
So ants蚂蚁 are using运用 interactions互动 in different不同 ways方法
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所以蚂蚁在不同的环境下
13:40
in a huge巨大 variety品种 of environments环境,
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2602
使用了完全不同的交互算法.
13:43
and we could learn学习 from this
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我们能够从中学习
13:45
about other systems系统 that operate操作
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并将结果用于那些没有
13:47
without central中央 control控制.
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中央控制的系统.
13:49
Using运用 only simple简单 interactions互动,
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1979
仅仅通过简单的接触,
13:51
ant蚂蚁 colonies群落 have been performing执行
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蚂蚁已经创造了
13:53
amazing惊人 feats功勋 for more than 130 million百万 years年份.
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长达1.3亿年的伟大历史.
13:56
We have a lot to learn学习 from them.
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我们还有很多需要向它们学习.
13:58
Thank you.
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感谢大家.
14:01
(Applause掌声)
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(掌声)
Translated by Psycho Decoder
Reviewed by Fang Yi

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ABOUT THE SPEAKER
Deborah Gordon - Ecologist
By studying how ant colonies work without any one leader, Deborah Gordon has identified striking similarities in how ant colonies, brains, cells and computer networks regulate themselves.

Why you should listen

Ecologist Deborah M. Gordon has learned that ant colonies can work without central control by using simple interactions like how often the insects touch antennae. Contrary to the notion that colonies are organized by efficient ants, she has instead discovered that evolution has produced “noisy” systems that tolerate accident and respond flexibly to the environment. When conditions are tough, natural selection favors colonies that conserve resources.

Her studies of ant colonies have led her and her Stanford colleagues to the discovery of the “Anternet,” which regulates foraging in ants in the same way the internet regulates data traffic. But as she said to Wired in 2013, "Insect behavior mimicking human networks ... is actually not what’s most interesting about ant networks. What’s far more interesting are the parallels in the other direction: What have the ants worked out that we humans haven’t thought of yet?" Her latest exploration: How do ants behave in space?

More profile about the speaker
Deborah Gordon | Speaker | TED.com