swarm intelligence托福聽(tīng)力原文翻譯及問(wèn)題答案

swarm intelligence托福聽(tīng)力原文翻譯及問(wèn)題答案

一、swarm intelligence 托福聽(tīng)力原文：

NARRATOR: Listen to part of a lecture in a biology class.

FEMALE PROFESSOR: I'd like to continue our discussion of animal behavior and start off today's class by focusing on a concept we haven't yet touched upon—swarm intelligence.Swarm intelligence is a collective behavior that emerges from a group of animals, like a colony of termites, a school of fish, or a flock of birds. Let's first consider the principles behind swarm intelligence, and we'll use the ant as our model.

Now, an ant on its own is not that smart. When you have a group of ants, however, there you have efficiency in action. You see, there's no leader running an ant colony. Each individual, each individual ant operates by instinctively following a simple set of rules when foraging for food.

Rule number 1: Deposit a chemical marker … called a pheromone. And rule 2: Follow the strongest pheromone path. The strongest pheromone path is advantageous to ants seeking food.

So, for example, when ants leave the nest, they deposit a pheromone trail along the route they take.  If they find food, they return to the nest on the same path and the pheromone trail gets stronger—it's doubled in strength.Because an ant that took a shorter path returns first, its pheromone trail is stronger, and other ants will follow it, according to rule 2. And as more ants travel that path, the pheromone trail gets even stronger.

So, what's happening here? Each ant follows two very basic rules, and each ant acts on information it finds in its immediate local environment. And it's important to note: Even though none of the individual ants is aware of the bigger plan, they collectively choose the shortest path between the nest and a food source because it's the most reinforced path.

By the way, a-a few of you have asked me about the relevance of what we're studying to everyday life. And swarm intelligence offers several good examples of how concepts in biology can be applied to other fields.

Well, businesses have been able to use this approach of following simple rules when designing complex systems, for instance, in telephone networks. When a call is placed from one city to another, it has to connect through a number of nodes along the way. At each point, a decision has to be made: Which direction does the call go from here? Well, a computer program was developed to answer this question based on rules that are similar to the ones that ants use to find food. Remember, individual ants deposit pheromones, and they follow the path that is most reinforced.

Now, in the phone network, a computer monitors the connection speed of each path, and identifies the paths that are currently the fastest —the least crowded parts of the network. And this information, converted into a numeric code, is deposited at the network nodes. This reinforces the paths that are least crowded at the moment. The rule the telephone network follows is to always select the path that is most reinforced. So, similar to the ant's behavior, at each intermediate node, the call follows the path that is most reinforced. This leads to an outcome which is beneficial to the network as a whole, and calls get through faster.But getting back to animal behavior, another example of swarm intelligence is the way flocks of birds are able to fly together so cohesively. How do they coordinate their movements and know where they're supposed to be?

Well, it basically boils down to three rules that each bird seems to follow. Rule 1: Stay close to nearby birds. Rule 2: Avoid collision with nearby birds. And rule 3: Move in the average speed and direction of nearby birds.

Oh, and by the way, if you're wondering how this approach can be of practical use for humans: The movie industry had been trying to create computer-generated flocks of birds in movie scenes.

The question was how to do it easily on a large scale? A researcher used these three rules in a computer graphics program, and it worked!There have also been attempts to create computer-generated crowds of people using this bird flocking model of swarm intelligence.

However, I'm not surprised that more research is needed. The three rules I mentioned might be great for bird simulations, but they don't take into account the complexity and unpredictability of human behavior. So, if you want to create crowds of people in a realistic way, that computer model might be too limited.

二、swarm intelligence 托福聽(tīng)力中文翻譯：

旁白：在生物課上聽(tīng)一節(jié)課的一部分。

女教授：我想繼續(xù)我們對(duì)動(dòng)物行為的討論，并從今天的課程開(kāi)始，重點(diǎn)討論一個(gè)我們尚未涉及到的群體智能概念。群體智能是一群動(dòng)物的集體行為，比如一群白蟻、一群魚(yú)或一群鳥(niǎo)。讓我們首先考慮群體智能背后的原理，我們將使用螞蟻?zhàn)鳛槲覀兊哪Ｐ汀?/p>

現(xiàn)在，一只螞蟻?zhàn)约翰](méi)有那么聰明。然而，當(dāng)你有一群螞蟻時(shí)，你就有了行動(dòng)的效率。你看，沒(méi)有領(lǐng)導(dǎo)者管理蟻群。每只螞蟻，每只螞蟻在覓食時(shí)都會(huì)本能地遵循一套簡(jiǎn)單的規(guī)則。

規(guī)則1：放置一種化學(xué)標(biāo)記物…叫做信息素。規(guī)則2：遵循最強(qiáng)的信息素路徑。最強(qiáng)的信息素路徑有利于螞蟻尋找食物。

例如，當(dāng)螞蟻離開(kāi)巢穴時(shí)，它們會(huì)沿著所走的路線留下信息素痕跡。如果它們找到食物，它們會(huì)回到同一條路徑上的巢穴，信息素的蹤跡會(huì)變得更強(qiáng)，強(qiáng)度會(huì)加倍。根據(jù)規(guī)則2，因?yàn)樽咻^短路徑的螞蟻會(huì)首先返回，所以它的信息素軌跡會(huì)更強(qiáng)，其他螞蟻會(huì)跟隨它。隨著越來(lái)越多的螞蟻沿著這條路徑行進(jìn)，信息素的蹤跡變得更加強(qiáng)大。

那么，這里發(fā)生了什么？每只螞蟻都遵循兩條非?；镜囊?guī)則，每只螞蟻都會(huì)根據(jù)在其直接的局部環(huán)境中找到的信息采取行動(dòng)。重要的是要注意：盡管沒(méi)有一只螞蟻知道更大的計(jì)劃，但它們會(huì)集體選擇巢穴和食物來(lái)源之間的最短路徑，因?yàn)檫@是最強(qiáng)化的路徑。

順便說(shuō)一下，你們中的一些人問(wèn)過(guò)我，我們正在學(xué)習(xí)的內(nèi)容與日常生活的相關(guān)性。群體智能提供了幾個(gè)很好的例子，說(shuō)明了如何將生物學(xué)中的概念應(yīng)用到其他領(lǐng)域。

嗯，企業(yè)已經(jīng)能夠在設(shè)計(jì)復(fù)雜系統(tǒng)時(shí)使用這種遵循簡(jiǎn)單規(guī)則的方法，例如在電話網(wǎng)絡(luò)中。當(dāng)一個(gè)電話從一個(gè)城市打到另一個(gè)城市時(shí)，它必須通過(guò)沿途的多個(gè)節(jié)點(diǎn)進(jìn)行連接。在每一點(diǎn)上，都必須做出決定：電話從這里往哪個(gè)方向走？嗯，一個(gè)計(jì)算機(jī)程序被開(kāi)發(fā)出來(lái)來(lái)回答這個(gè)問(wèn)題，它基于的規(guī)則與螞蟻用來(lái)尋找食物的規(guī)則相似。記住，單個(gè)螞蟻會(huì)沉積信息素，它們會(huì)沿著最強(qiáng)化的路徑前進(jìn)。

現(xiàn)在，在電話網(wǎng)絡(luò)中，計(jì)算機(jī)監(jiān)控每條路徑的連接速度，并識(shí)別當(dāng)前最快的路徑，即網(wǎng)絡(luò)中最不擁擠的部分。這些信息被轉(zhuǎn)換成數(shù)字代碼，存儲(chǔ)在網(wǎng)絡(luò)節(jié)點(diǎn)上。這加強(qiáng)了目前最不擁擠的道路。電話網(wǎng)絡(luò)遵循的規(guī)則是始終選擇最加固的路徑。因此，與螞蟻的行為類似，在每個(gè)中間節(jié)點(diǎn)上，調(diào)用遵循最強(qiáng)化的路徑。這將導(dǎo)致對(duì)整個(gè)網(wǎng)絡(luò)有利的結(jié)果，并且通話速度更快。但回到動(dòng)物行為上來(lái)，群體智能的另一個(gè)例子是成群的鳥(niǎo)能夠如此緊密地飛行在一起。他們?nèi)绾螀f(xié)調(diào)自己的動(dòng)作，知道自己應(yīng)該在哪里？

嗯，基本上可以歸結(jié)為每只鳥(niǎo)似乎都遵循的三條規(guī)則。規(guī)則1：靠近附近的鳥(niǎo)類。規(guī)則2：避免與附近的鳥(niǎo)類發(fā)生碰撞。規(guī)則3：以附近鳥(niǎo)類的平均速度和方向移動(dòng)。

哦，順便說(shuō)一句，如果你想知道這種方法如何對(duì)人類實(shí)用：電影業(yè)一直試圖在電影場(chǎng)景中創(chuàng)造計(jì)算機(jī)生成的鳥(niǎo)群。

問(wèn)題是如何在大規(guī)模上輕松做到這一點(diǎn)？一位研究人員在一個(gè)計(jì)算機(jī)圖形程序中使用了這三條規(guī)則，并且成功了！也有人試圖利用這種群體智能的鳥(niǎo)群模型來(lái)創(chuàng)造計(jì)算機(jī)生成的人群。

然而，我并不驚訝需要更多的研究。我提到的三條規(guī)則對(duì)于鳥(niǎo)類模擬可能很有用，但它們沒(méi)有考慮到人類行為的復(fù)雜性和不可預(yù)測(cè)性。所以，如果你想以一種真實(shí)的方式創(chuàng)造人群，那么這個(gè)計(jì)算機(jī)模型可能太有限了。

三、swarm intelligence 托福聽(tīng)力問(wèn)題：

Q1:1.What is the lecture mainly about?

A. Various methods that ants use to locate food

B. A collective behavior common to humans and animals

C. A type of animal behavior and its application by humans

D. Strategies that flocks of birds use to stay in formation

Q2:2.According to the professor, what behavior plays an important role in the way ants obtain food?

A. Ants usually take a different path when they return to their nest.

B. Ants leave chemical trails when they are outside the nest.

C. Small groups of ants search in different locations.

D. Ants leave pieces of food along the path as markers.

Q3:3.What are two principles of swarm intelligence based on the ant example? [Click on 2 answers.]

A. Individuals are aware of the group goal.

B. Individuals act on information in their local environment.

C. Individuals follow a leader's guidance.

D. Individuals instinctively follow a set of rules.

Q4:4.According to the professor, what path is followed by both telephone calls on a network and ants seeking food?

A. The path with the least amount of activity

B. The most crowded path

C. The path that is most reinforced

D. The path that has intermediate stopping points

Q5:5.Why does the professor mention movies?

A. To identify movie scenes with computer-simulated flocks of birds

B. To identify a good source of information about swarm intelligence

C. To emphasize how difficult it still is to simulate bird flight

D. To explain that some special effects in movies are based on swarm intelligence

Q6:6.What is the professor's attitude about attempts to create computer-generated crowds of people?

A. She believes that the rules of birds' flocking behavior do not apply to group behavior in humans.

B. She thinks that crowd scenes could be improved by using the behavior of ant colonies as a model.

C. She is surprised by how realistic the computer-generated crowds are.

D. She is impressed that computer graphics can create such a wide range of emotions.

四、swarm intelligence 托福聽(tīng)力答案：

A1:正確答案：C

A2:正確答案：B

A3:正確答案：BD

A4:正確答案：C

A5:正確答案：D

A6:正確答案：A

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