Inside the ant colony Deborah M. Gordon

Think about all the things that need to happen

for a human settlement to thrive:

obtaining food,

building shelter,

raising children and more.

There needs to be a way to divide resources,

organize major efforts

and distribute labor efficiently.

Now imagine having to do this without any sort of planning

or higher level communication.

Welcome to the ant colony.

Ants have some of the most complex social organization

in the animal kingdom,

living in structured colonies

containing different types of members

who perform specific roles.

But although this may sound similar to some human societies,

this organization doesn’t arise from any higher level decisions,

but is part of a biologically programmed cycle.

In many species,

all the winged males and winged virgin queens

from all the nearby colonies in the population

each leave from their different nests

and meet at a central place to mate,

using pheromones to guide each other to a breeding ground.

After mating, the males die off,

while females try to establish a new colony.

The few that are successful settle down in a suitable spot,

lose their wings,

and begin laying eggs,

selectively fertilizing some using stored sperm they’ve saved up from mating.

Fertilized eggs grow into female workers

who care for the queen and her eggs.

They will then defend the colony

and forage for food,

while unfertilized eggs grow into males

whose only job is to wait until they are ready to leave the nest

and reproduce, beginning the cycle again.

So how do worker ants decide what to do and when?

Well, they don’t really.

Although they have no methods of intentional communication,

individual ants do interact with one another

through touch, sound and chemical signals.

These stimuli accomplish many things

from serving as an alarm to other ants if one is killed,

to signaling when a queen is nearing the end of her reproductive life.

But one of the most impressive collective capabilities of an ant colony

is to thoroughly and efficiently explore large areas

without any predetermined plan.

Most species of ants have little or no sense of sight

and can only smell things in their vicinity.

Combined with their lack of high level coordination,

this would seem to make them terrible explorers,

but there is an amazingly simple way

that ants maximize their searching efficiency;

by changing their movement patterns

based on individual interactions.

When two ants meet,

they sense each other by touching antennae.

If there are many ants in a small area this will happen more often

causing them to respond by moving

in more convoluted, random paths in order to search more thoroughly.

But in a larger area, with less ants, where such meetings happen less often,

they can walk in straight lines to cover more ground.

While exploring their environment in this way,

an ant may come across any number of things,

from threats or enemies, to alternate nesting sites.

And some species have another capability known as recruitment.

When one of these ants happens to find food,

it will return with it, marking its path with a chemical scent.

Other ants will then follow this pheromone trail,

renewing it each time they manage to find food and return.

Once the food in that spot is depleted,

the ants stop marking their return.

The scent dissipates and ants are no longer attracted to that path.

These seemingly crude methods of search and retrieval

are, in fact, so useful that they are applied in computer models

to obtain optimal solutions from decentralized elements,

working randomly and exchanging simple information.

This has many theoretical and practical applications,

from solving the famous traveling salesman problem,

to scheduling computing tasks and optimizing Internet searches,

to enabling groups of robots to search a minefield

or a burning building collectively, without any central control.

But you can observe these fascinatingly simple, yet effective, processes directly

through some simple experiments,

by allowing ants to enter empty spaces of various sizes

and paying attention to their behavior.

Ants may not be able to vote, hold meetings or even make any plans,

but we humans may still be able to learn something

from the way that such simple creatures

are able to function so effectively in such complex ways.

想想

人类住区蓬勃发展需要发生的所有事情:

获得食物、

建造庇护所、

抚养孩子等等。

需要有一种方法来分配资源、

组织重大工作

并有效地分配劳动力。

现在想象一下,在没有任何计划

或更高级别沟通的情况下必须这样做。

欢迎来到蚁群。

蚂蚁拥有动物王国中一些最复杂的社会

组织,

生活在结构化的群体中,

其中包含不同类型的成员

,这些成员扮演着特定的角色。

但是,尽管这听起来可能与某些人类社会相似,但

这种组织并非来自任何更高层次的决策,

而是生物程序循环的一部分。

在许多物种中,种群中所有附近殖民地的

所有有翅膀的雄性和有翅膀的处女女王

从不同的巢穴中离开,

并在一个中心地点相遇交配,

使用信息素将彼此引导到繁殖地。

交配后,雄性死亡,

而雌性试图建立一个新的殖民地。

少数成功地在合适的地方安顿下来,

失去翅膀

,开始产卵,

使用他们从交配中积攒下来的储存精子选择性地使一些受精。

受精卵成长为

照顾女王和她的卵的女工。

然后它们将保卫殖民地

并觅食,

而未受精的卵长成雄性

,它们唯一的工作就是等到它们准备好离开巢穴

并繁殖,再次开始循环。

那么工蚁如何决定什么时候做什么?

好吧,他们真的没有。

尽管它们没有有意交流的方法,但

个体蚂蚁确实

通过触摸、声音和化学信号相互交流。

这些刺激完成了许多事情,

从在一只蚂蚁被杀死时向其他蚂蚁发出警报,到在蚁后

接近生殖生命结束时发出信号。

但是蚁群最令人印象深刻的集体能力之一

就是在没有任何预定计划的情况下彻底有效地探索大片区域

大多数种类的蚂蚁几乎没有或没有视觉

,只能闻到附近的东西。

再加上它们缺乏高度协调,

这似乎使它们成为可怕的探索者,

但蚂蚁有一种非常简单的方法

可以最大限度地提高搜索效率;

通过根据个人互动改变他们的运动模式

当两只蚂蚁相遇时,

它们通过触角相互感应。

如果在一个小区域内有很多蚂蚁,这种情况会更频繁地发生,

导致它们通过

移动更复杂、更随机的路径来做出反应,以便更彻底地搜索。

但是在更大的区域,蚂蚁较少,这种会议发生的频率较低,

它们可以直线行走以覆盖更多的地面。

在以这种方式探索它们的环境时,

一只蚂蚁可能会遇到许多事情,

从威胁或敌人到交替的筑巢地点。

有些物种还有另一种称为招募的能力。

当其中一只蚂蚁碰巧找到食物时,

它会带着它回来,用化学气味标记它的路径。

然后其他蚂蚁将跟随这条信息素轨迹,

每次它们设法找到食物并返回时都会更新它。

一旦该地点的食物耗尽

,蚂蚁就会停止标记它们的返回。

气味消散,蚂蚁不再被那条路径吸引。

这些看似粗糙的搜索和检索

方法实际上非常有用,以至于它们被应用于计算机模型中,

以从分散的元素中获得最佳解决方案,

随机工作并交换简单的信息。

这具有许多理论和实际应用,

从解决著名的旅行商问题,

到调度计算任务和优化互联网搜索,

再到使机器人组能够在

没有任何中央控制的情况下集体搜索雷区或燃烧的建筑物。

但是你可以通过一些简单的实验直接观察这些非常简单但有效的过程

,让蚂蚁进入各种大小的空白空间

并注意它们的行为。

蚂蚁可能无法投票、召开会议甚至制定任何计划,

但我们人类仍然可以

从这些简单的

生物能够以如此复杂的方式如此有效地发挥作用的方式中学到一些东西。