The Smart Swarm

by Peter Miller?

The study of swarms is providing insights that can help humans manage complex systems, from online search engines to military robots.

從網(wǎng)絡(luò)搜索引擎到軍用機(jī)器人华嘹，研究集群讓人類(lèi)在?管理與運(yùn)用復(fù)雜系統(tǒng)上又更進(jìn)一步。

How do the simple actions of individuals add up to the complex behaviour of a group? How do hundreds of honeybees make a critical decision about their hive if many of them disagree? What enables a school of herring to coordinate its movements so precisely it can change direction in a flash, like a single, silvery organism? The answer has to do with a remarkable phenomenon I call smart swarm.

簡(jiǎn)單的個(gè)體動(dòng)作如何組成復(fù)雜的群體行為丧裁？如果上百只蜜蜂無(wú)法達(dá)成一致礁阁，它們?cè)鯓用髦堑貨Q定蜂巢應(yīng)該建在哪里巧号？為什么一群鯡魚(yú)能精準(zhǔn)地相互協(xié)調(diào)，像一尾銀色的有機(jī)體來(lái)去自如姥闭？這些問(wèn)題的答案與一個(gè)有趣的自然現(xiàn)象有關(guān)丹鸿，我稱(chēng)之為：智群。

A smart swarm is a group of individuals who respond to one another and to their environment in ways that give them power, as a group to cope with uncertainty, complexity, and change. Take birds, for example. There's a small park near the White House in Washington, D.C., where I like to watch flocks of pigeons swirl over the traffic and trees. Sooner or later, the birds come to rest on ledges of buildings surrounding the park. Then something disrupts them, and they're off again in synchronised flight.

智群是指通過(guò)組成集體來(lái)應(yīng)對(duì)不確定性棚品、復(fù)雜性與變化因素靠欢、能對(duì)環(huán)境與同伴作出反應(yīng)并以此增強(qiáng)力量的一群個(gè)體。比如說(shuō)鳥(niǎo)吧铜跑。華盛頓的白宮附近有一個(gè)小公園门怪，我喜歡在那里看鴿群在車(chē)流與樹(shù)木上空盤(pán)旋。有時(shí)候锅纺，它們會(huì)在公園周?chē)姆块苤揽铡⒋翱蛏贤Ｏ滦菹ⅰＨ绻惺裁礀|西驚擾了它們，它們又會(huì)不約而同地集體起飛坦弟。

The birds don't have a leader. No pigeon is telling the others what to do. Instead, they're each paying close attention to the pigeons next to them, each bird following simple rules as they wheel across the sky. These rules add up to another kind of swarm intelligence—one that has less to do with making decisions than with precisely coordinating movement.

這些鴿子沒(méi)有領(lǐng)頭者护锤。不會(huì)有哪只鴿子指揮它們接下來(lái)做什么。事實(shí)上酿傍，它們僅僅是密切關(guān)注旁邊的鴿子在做什么烙懦，在空中急轉(zhuǎn)彎的時(shí)候遵循簡(jiǎn)單的規(guī)則。這些規(guī)則形成了另一種群體智慧——個(gè)體不做決定而是專(zhuān)注于精確的動(dòng)作配合赤炒。

Craig Reynolds, a computer graphics researcher, was curious about what these rules might be. So, in 1986, he created a deceptively simple steering program called boids. In this simulation, generic birdlike objects, or boids, were each given three instructions: 1) avoid crowding nearby boids, 2) fly in the average direction of nearby boids, and 3) stay close to nearby boids. The result, when set in motion on a computer screen, was a convincing simulation of flocking, including lifelike and unpredictable movements.

計(jì)算機(jī)圖形學(xué)家Craig Reynolds很好奇這些背后的規(guī)則到底是什么氯析。所以，他在1986年開(kāi)發(fā)了看似簡(jiǎn)單的導(dǎo)向程序boids莺褒。在此模擬過(guò)程中魄鸦，每個(gè)設(shè)計(jì)成鳥(niǎo)類(lèi)形狀的物體，也就是boids癣朗，都收到三個(gè)指令：1）與周邊的boids保持一定遠(yuǎn)的距離以避免擠壓拾因，2）以周邊boids的平均方向作為飛行方向，3）與周邊的boids保持一定近的距離以保持隊(duì)形旷余。從電腦屏幕上的運(yùn)行情況來(lái)看绢记，這一試驗(yàn)的最終動(dòng)態(tài)，包括栩栩如生又不可人為預(yù)測(cè)的各種動(dòng)作正卧，正是對(duì)鳥(niǎo)群群集的成功模擬蠢熄。

At the time, Reynolds was looking for ways to depict animals realistically in TV shows and films. (Batman Returns in 1992 was the first movie to use his approach, portraying a swarm of bats and an army of penguins.) Today he works at Sony doing research for games, such as an algorithm that simulates in real time as many as 15,000 interacting birds, fish, or people.

當(dāng)時(shí)，Reynolds在尋找在電視和電影中逼真描繪動(dòng)物的方法炉旷。（1992年的《蝙蝠俠歸來(lái)(Batman Returns)》是第一部運(yùn)用其想法的電影签孔，影片中描繪了一群蝙蝠和一隊(duì)企鵝）如今他在索尼公司從事游戲研究，開(kāi)發(fā)例如能夠?qū)崟r(shí)模擬多達(dá)15000只相互交流的鳥(niǎo)窘行、魚(yú)或人所組成的群體的算法饥追。

By demonstrating the power of self-organizing models to mimic swarm behaviour, Reynolds was also blazing the trail for robotics engineers. A team of robots that could coordinate its actions like a flock of birds could offer significant advantages over a solitary robot. Spread out over a large area, a group could function as a powerful mobile sensor net, gathering information about what's out there. If the group encountered something unexpected, it could adjust and respond quickly, even if the robots in the group weren't very sophisticated, just as ants are able to come up with various options by trial and error. If one member of the group were to break down, others could take its place. And, most important, control of the group could be decentralized, not dependent on a leader.

Reynolds向世人展現(xiàn)了自控模型在模擬群體行為方面的潛力，為?研究機(jī)器人技術(shù)的工程師們開(kāi)辟了新的研究方向罐盔。相比單個(gè)機(jī)器人但绕，能夠像鳥(niǎo)群一樣協(xié)作的機(jī)器人組顯然具有巨大優(yōu)勢(shì)。它們能分散并覆蓋大面積區(qū)域惶看，形成強(qiáng)大的移動(dòng)傳感網(wǎng)絡(luò)捏顺，收集外界的信息。若遇到突發(fā)情況纬黎，集群能夠快速調(diào)整應(yīng)對(duì)幅骄，哪怕是相對(duì)簡(jiǎn)易的機(jī)器人組，也能像螞蟻一樣通過(guò)不斷試驗(yàn)找到解決之道本今。要是集群中的一個(gè)個(gè)體掉鏈子拆座，其它成員能夠及時(shí)填補(bǔ)空缺主巍。最重要的是，整個(gè)集群的控制權(quán)是分散的懂拾，不必集中于領(lǐng)袖煤禽。

"In biology, if you look at groups with large numbers, there are very few examples where you have a central agent," says Vijay Kumar, a professor of mechanical engineering at the University of Pennsylvania. "Everything is very distributed: They don't all talk to each other. They act on local information. And they're all anonymous. I don't care who moves the chair, as long as somebody moves the chair. To go from one robot to multiple robots, you need all three of those ideas."

“生物學(xué)中铐达，你會(huì)發(fā)現(xiàn)大數(shù)量群體中有中心領(lǐng)導(dǎo)者的其實(shí)不多岖赋，”賓夕法尼亞大學(xué)機(jī)械工程學(xué)教授Vijay Kumar說(shuō)，“一切都是分散的：它們不會(huì)跟彼此講話瓮孙。它們根據(jù)周邊數(shù)據(jù)行動(dòng)唐断。個(gè)體特征被忽略。我不管是誰(shuí)做的杭抠，只要有人做就行脸甘。從單個(gè)機(jī)器人推廣到多個(gè)機(jī)器人，這三點(diǎn)都很重要偏灿〉ぞ鳎”

Within five years Kumar hopes to put a networked team of robotic vehicles in the field. One purpose might be as first responders. "Let's say there's a 911 call," he says. "The fire alarm goes off. You don't want humans to respond. You want machines to respond, to tell you what's happening. Before you send firemen into a burning building, why not send in a group of robots?"

Kumar希望在五年內(nèi)推出一個(gè)網(wǎng)絡(luò)化協(xié)作的機(jī)器人車(chē)組。其中一個(gè)主要目標(biāo)是用作一線應(yīng)援翁垂∶猓“比如說(shuō)現(xiàn)在有人打911呼救，”他說(shuō)沿猜，“火警警報(bào)響了枚荣。你不想讓人去應(yīng)援，想讓機(jī)器去查看情況啼肩。在消防隊(duì)進(jìn)入著火的樓之前橄妆，為什么不讓一組機(jī)器人先去呢？”

Taking this idea one step further, Marco Dorigo's group in Brussels is leading a European effort to create a "swarmanoid," a group of cooperating robots with complementary abilities: "foot-bots" to transport things on the ground, "hand-bots" to climb walls and manipulate objects, and "eye-bots" to fly around, providing information to the other units.

布魯塞爾的Marco Dorigo團(tuán)隊(duì)則更進(jìn)一步祈坠。這群歐洲人嘗試開(kāi)發(fā)名為“swarmanoid”的分工協(xié)作式機(jī)器人組：“foot-bots”負(fù)責(zé)地面物體的傳運(yùn)害碾，“hand-bots”能攀援墻面與操作物體，“eye-bots”可以飛來(lái)飛去赦拘，為其他部門(mén)提供數(shù)據(jù)信息蛮原。

The military is eager to acquire similar capabilities. On January 20, 2004, researchers released a swarm of 66 pint-size robots into an empty office building at Fort A. P. Hill, a training centre near Fredericksburg, Virginia. The mission: Find targets hidden in the building.

軍方對(duì)類(lèi)似應(yīng)用求之若渴。2004年1月20日弗吉尼亞的弗雷德里克斯堡附近另绩，研究人員在Fort A. P. Hill訓(xùn)練中心的空辦公樓中測(cè)試由66個(gè)小型機(jī)器人組成的機(jī)器人集群儒陨。它們的任務(wù)是：在大樓中找到隱藏的目標(biāo)。

Zipping down the main hallway, the foot-long (30 cm) red robots pivoted this way and that on their three wheels, resembling nothing so much as large insects. Eight sonars on each unit helped them avoid collisions with walls and other robots. As they spread out, entering one room after another, each robot searched for objects of interest with a small, Web-style camera. When one robot encountered another, it used wireless network gear to exchange information. ("Hey, I've already explored that part of the building. Look somewhere else.")

這些30厘米長(zhǎng)的紅色機(jī)器人在主廊道上迅速移動(dòng)笋籽，靠三個(gè)輪子靈巧轉(zhuǎn)向蹦漠，酷似巨大的昆蟲(chóng)。每個(gè)?部件上都裝有八個(gè)雷達(dá)车海，以防與墻和其它機(jī)器人發(fā)生碰撞笛园。它們分頭行動(dòng)逐個(gè)搜查房間隘击，用網(wǎng)狀小鏡頭尋找可疑物品。兩個(gè)機(jī)器人相遇之后會(huì)通過(guò)無(wú)線網(wǎng)絡(luò)裝置?交流情報(bào)研铆。（“嘿埋同，那邊我剛瞧過(guò)了，去別處看看棵红⌒琢蓿”）

In the back of one room, a robot spotted something suspicious: a pink ball in an open closet (the swarm had been trained to look for anything pink). The robot froze, sending an image to its human supervisor. Soon several more robots arrived to form a perimeter around the pink intruder. Within half an hour, all six of the hidden objects had been found. The research team conducting the experiment declared the run a success. Then they started a new test.

在其中一個(gè)房間后方，一個(gè)機(jī)器人發(fā)現(xiàn)了可疑情況：在打開(kāi)的衣柜里有一個(gè)粉紅色的球（它們的目標(biāo)是尋找一切粉紅色的東西）逆甜。這個(gè)機(jī)器人呆住虱肄，給人類(lèi)管理者發(fā)了張照片。不久交煞，一些機(jī)器人也來(lái)到這間房子咏窿，在粉紅色入侵者的周?chē)鷩藗€(gè)圓。半個(gè)小時(shí)之內(nèi)素征，藏匿的六個(gè)目標(biāo)全部被找到集嵌。開(kāi)展實(shí)驗(yàn)的研究團(tuán)隊(duì)宣布實(shí)驗(yàn)成功。之后他們又開(kāi)始了新的嘗試御毅。

The demonstration was part of the Centibots project, an investigation to see if as many as a hundred robots could collaborate on a mission. If they could, teams of robots might someday be sent into a hostile village to flush out terrorists or locate prisoners; into an earthquake-damaged building to find victims; onto chemical-spill sites to examine hazardous waste; or along borders to watch for intruders. Military agencies such as DARPA (Defence Advanced Research Projects Agency) have funded a number of robotics programs using collaborative flocks of helicopters and fixed-wing aircraft, schools of torpedo-shaped underwater gliders, and herds of unmanned ground vehicles. But at the time, this was the largest swarm of robots ever tested.

這次實(shí)踐是Centibots項(xiàng)目的一部分根欧，研究多達(dá)一百個(gè)機(jī)器人能否合作完成一個(gè)任務(wù)。如果能亚享，機(jī)器人組將來(lái)可能會(huì)被派往敵方村落排查恐怖分子咽块、確定囚犯位置，到受震房屋里尋找傷者欺税，到化學(xué)物質(zhì)泄漏區(qū)調(diào)查有毒有害物排放侈沪，又或者在邊境偵查入侵者。軍事機(jī)構(gòu)晚凿，比如說(shuō)DARPA（美國(guó)國(guó)防高級(jí)研究計(jì)劃局）亭罪，資助了包括合作型智群理念下的直升機(jī)組、固定翼機(jī)組歼秽、魚(yú)雷狀水下滑翔機(jī)組应役、無(wú)人地面車(chē)組在內(nèi)的一系列機(jī)器人研究項(xiàng)目。但在當(dāng)時(shí)燥筷，這已經(jīng)是試驗(yàn)過(guò)的最大型集群了箩祥。

"When we started Centibots, we were all thinking, this is a crazy idea, it's impossible to do," says Régis Vincent, a researcher at SRI International in Menlo Park, California. “Now we're looking to see if we can do it with a thousand robots."

“當(dāng)我們開(kāi)始做Centibots項(xiàng)目的時(shí)候，我們都覺(jué)得：這太瘋狂了肆氓，根本不可能做到袍祖，”加州門(mén)羅公園的斯坦福國(guó)際咨詢(xún)研究所研究人員Régis Vincent說(shuō)，“而現(xiàn)在我們希望試試我們能不能做到一千個(gè)機(jī)器人谢揪〗堵”

In nature, of course, animals travel in even larger numbers.

當(dāng)然自然界中的動(dòng)物們甚至以更大數(shù)量的群體遷移捐凭。

That's because, as members of a big group, whether it's a flock, school, or herd, individuals increase their chances of detecting predators, finding food, locating a mate, or following a migration route. For these animals, coordinating their movements with one another can be a matter of life or death.

這是因?yàn)闊o(wú)論是鳥(niǎo)群、魚(yú)群還是羊群凳鬓，大集體能夠更好地發(fā)現(xiàn)天敵茁肠、食物、伴侶缩举，也更容易跟隨遷移的路線垦梆。對(duì)這些動(dòng)物來(lái)說(shuō)，彼此間動(dòng)作協(xié)調(diào)事關(guān)生死蚁孔。

"It's much harder for a predator to avoid being spotted by a thousand fish than it is to avoid being spotted by one," says Daniel Grünbaum, a biologist at the University of Washington. “News that a predator is approaching spreads quickly through a school because fish sense from their neighbours that something's going on."

“一千只魚(yú)比一只魚(yú)更容易發(fā)現(xiàn)捕食者奶赔，”華盛頓大學(xué)生物學(xué)家Daniel Grünbaum說(shuō)惋嚎，“捕食者正在靠近的消息能在魚(yú)群中迅速傳開(kāi)杠氢，因?yàn)轸~(yú)可以從身邊的同伴那里感受到危險(xiǎn)信號(hào)×砦椋”

When a predator strikes a school of fish, the group is capable of scattering in patterns that make it almost impossible to track any individual. It might explode in a flash, create a kind of moving bubble around the predator, or fracture into multiple blobs, before coming back together and swimming away. That's the wonderful appeal of swarm intelligence. Whether we’re talking about ants, bees, pigeons, or caribou, the ingredients of smart group behavior—decentralised control, response to local cues, simple rules of thumb—add up to a shrewd strategy to cope with complexity.

捕食者攻擊魚(yú)群的時(shí)候鼻百，魚(yú)群能迅速分散以至于捕食者幾乎不可能追到任何一只。魚(yú)群就像是瞬間爆炸摆尝，在捕食者周?chē)圃煲苿?dòng)氣泡温艇，或者分裂成無(wú)數(shù)小點(diǎn)，然后重新集聚再游走堕汞。這就是群體智慧的非凡魅力勺爱。不管是螞蟻、蜜蜂讯检、鴿子還是馴鹿琐鲁，智群行為的要素——分散化控制模式、關(guān)注周邊信息的反應(yīng)模式和簡(jiǎn)單的經(jīng)驗(yàn)規(guī)則——組成了能夠應(yīng)對(duì)復(fù)雜變化的機(jī)智策略人灼。

"We don't even know yet what else we can do with this," says Eric Bonabeau, a complexity theorist and the chief scientist at Icosystem Corporation in Cambridge, Massachusetts. "We're not used to solving decentralised problems in a decentralised way. We can't control an emergent phenomenon like traffic by putting stop signs and lights everywhere. But the idea of shaping traffic as a self-organizing system, that’s very exciting."

“我們甚至不知道還能怎么做围段，”馬薩諸塞劍橋Icosystem公司復(fù)雜理論學(xué)家、首席科學(xué)家Eric Bonabeau說(shuō)投放，“我們還不適應(yīng)用分散化的方法解決分散化問(wèn)題奈泪。我們不能用到處放停止標(biāo)志牌和交通信號(hào)燈的方法來(lái)管理交通這樣的新興現(xiàn)象。但把交通變成自我調(diào)節(jié)系統(tǒng)的想法灸芳，確實(shí)非常有意思涝桅。”

Social and political groups have already adopted crude swarm tactics. During mass protests eight years ago in Seattle, anti-globalisation activists used mobile communications devices to spread news quickly about police movements, turning an otherwise unruly crowd into a “smart mob" that was able to disperse and re-form like a school of fish.

有的社會(huì)烙样、政治團(tuán)體已經(jīng)采用了智群策略冯遂，盡管尚不成熟。八年前西雅圖群眾抗議活動(dòng)中误阻，反全球化活動(dòng)者用移動(dòng)通訊設(shè)備快速發(fā)布警察動(dòng)態(tài)信息债蜜，把原本無(wú)組織的群眾變成能夠像魚(yú)群一樣分散和重組的“智能團(tuán)體”晴埂。

The biggest changes may be on the Internet. Consider the way Google uses group smarts to find what you're looking for. When you type in a search query, Google surveys billions of Web pages on its index servers to identify the most relevant ones. It then ranks them by the number of pages that link to them, counting links as votes (the most popular sites get weighted votes, since they're more likely to be reliable). The pages that receive the most votes are listed first in the search results. In this way, Google says, it “uses the collective intelligence of the Web to determine a page's importance.”

而最大的變化發(fā)生在互聯(lián)網(wǎng)上。試想Google是如何利用群體智能搜索你想找的內(nèi)容的寻定。當(dāng)你鍵入搜索指令后儒洛，Google在它的索引服務(wù)器上查閱數(shù)十億網(wǎng)頁(yè)來(lái)篩選出最有關(guān)聯(lián)的，然后將它們根據(jù)被鏈接數(shù)和權(quán)重（最熱門(mén)的網(wǎng)站相對(duì)重要狼速，因?yàn)樗鼈兏锌赡軠?zhǔn)確可靠）排序琅锻，最高票結(jié)果會(huì)排在搜索結(jié)果之首。由此向胡，Google說(shuō)它“利用網(wǎng)絡(luò)的集體智慧來(lái)決定網(wǎng)頁(yè)的重要程度”恼蓬。

Wikipedia, a free collaborative encyclopedia, has also proved to be a big success, with millions of articles in more than 200 languages about everything under the sun, each of which can be contributed by anyone or edited by anyone. "It's now possible for huge numbers of people to think together in ways we never imagined a few decades ago," says Thomas Malone of MIT's new Centre for Collective Intelligence. “No single person knows everything that's needed to deal with problems we face as a society, such as health care or climate change, but collectively we know far more than we've been able to tap so far."

事實(shí)證明維基百科獲得了巨大的成功，這個(gè)自由的協(xié)作式百科全書(shū)擁有超過(guò)兩百種語(yǔ)言寫(xiě)就僵芹、內(nèi)容涵蓋天下所有事物的數(shù)百萬(wàn)個(gè)詞條处硬，每個(gè)人都能貢獻(xiàn)和修改∧磁桑“如今大量用戶(hù)一起協(xié)作變成可能荷辕，這是在幾十年前不可想象的狀況〖悖”麻省理工學(xué)院新的集群智能中心的Thomas Malone說(shuō)疮方，“沒(méi)有哪個(gè)人能夠知道解決社會(huì)問(wèn)題的所有相關(guān)知識(shí)，比如說(shuō)醫(yī)療保障和氣候變化茧彤，但以綜合協(xié)作的方式骡显，我們就能獲得比我們目前所知更多的知識(shí)≡啵”

Such thoughts underline an important truth about collective intelligence: Crowds tend to be wise only if individual members act responsibly and make their own decisions. A group won't be smart if its members imitate one another, slavishly follow fads, or wait for someone to tell them what to do. When a group is being intelligent, whether it's made up of ants or attorneys, it relies on its members to do their own part. For those of us who sometimes wonder if it’s really worth recycling that extra bottle to lighten our impact on the planet, the bottom line is that our actions matter, even if we don't see how.?

以上想法突顯出一個(gè)關(guān)于集群智能的重要事實(shí)：只有當(dāng)個(gè)體成員表現(xiàn)得負(fù)責(zé)任并自主決定惫谤，群體才會(huì)有智慧。如果成員們只會(huì)互相模仿遭殉、盲目跟風(fēng)或者等待別人告訴自己應(yīng)該做什么石挂，一個(gè)群體就不可能成為智群。不管是螞蟻還是馴鹿险污，智能的群體需要每位成員做好自己的角色痹愚。我們之中有些人可能有時(shí)會(huì)疑惑多回收一個(gè)塑料瓶在減輕人類(lèi)對(duì)地球的作用上到底有多大用處，但最重要的是其實(shí)每一個(gè)動(dòng)作都會(huì)產(chǎn)生影響蛔糯，哪怕我們還不能理解它如何影響拯腮。

Wisdom of the Herd

牧群智能

Group behaviour can be vital for herd animals to avoid predators. Karsten Heuer, a wildlife biologist, and his wife, Leanne Allison, were studying a large caribou herd in Canada. When they spotted a wolf creeping toward the caribou, they noted that the herd responded with a classic swarm defence.?

群體行動(dòng)是牧群動(dòng)物用以防避捕食者的重要武器。野生動(dòng)物學(xué)家Karsten Heuer和他的妻子Leanne Allison曾在加拿大研究一大群馴鹿蚁飒。他們發(fā)現(xiàn)鹿群會(huì)在有狼準(zhǔn)備悄悄靠近的時(shí)候作出經(jīng)典的智群防御反應(yīng)动壤。

"The nearest caribou [to the wolf] turned and ran, and that response moved like a wave through the entire herd until they were all running.” Heuer said. Each animal turned and ran as the wolf approached it. In the end, the herd escaped over the ridge, and the wolf was left panting and gulping snow.

“（離狼）最近的馴鹿會(huì)轉(zhuǎn)向逃跑，這一反應(yīng)像波浪在整個(gè)鹿群中傳播開(kāi)來(lái)淮逻，最后所有的鹿都在逃跑琼懊「篝ぃ”Heuer說(shuō)。每一只馴鹿都開(kāi)始轉(zhuǎn)身逃跑哼丈，仿佛狼逼近的是自己启妹。最后，鹿群從山脊上逃離了醉旦，留下那只狼氣喘吁吁地吞雪止渴饶米。

The herd’s evasive manoeuvres displayed not panic, but precision. Every caribou knew when it was time to run and in which direction to go, even if it didn't know exactly why. No leader was responsible for coordinating the rest of the herd. Instead, each animal was following simple rules evolved over thousands of years of wolf attacks.

鹿群的逃避策略并不是風(fēng)聲鶴唳草木皆兵，反而表現(xiàn)出高準(zhǔn)確性车胡。每只馴鹿都知道當(dāng)時(shí)應(yīng)該逃跑檬输、往哪個(gè)方向跑，即使它并不清楚為什么要跑匈棘。不需要專(zhuān)門(mén)的領(lǐng)頭鹿協(xié)調(diào)調(diào)動(dòng)其他成員丧慈。事實(shí)上，數(shù)千年與狼的斗爭(zhēng)演化出一套簡(jiǎn)單的智群規(guī)則羹饰，而每一頭鹿只需要遵守就行了伊滋。

（譯自Integrated Study課教材Pathways4）