swarm intelligence托福听力原文翻译及问题答案
2023-05-18 18:15:24 来源:金宝搏188入口
swarm intelligence托福听力原文翻译及问题答案
一、swarm intelligence 托福听力原文:
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 托福听力中文翻译:
旁白:在生物课上听一节课的一部分。
女教授:我想继续我们对动物行为的讨论,并从今天的课程开始,重点讨论一个我们尚未涉及到的群体智能概念。群体智能是一群动物的集体行为,比如一群白蚁、一群鱼或一群鸟。让我们首先考虑群体智能背后的原理,我们将使用蚂蚁作为我们的模型。
现在,一只蚂蚁自己并没有那么聪明。然而,当你有一群蚂蚁时,你就有了行动的效率。你看,没有领导者管理蚁群。每只蚂蚁,每只蚂蚁在觅食时都会本能地遵循一套简单的规则。
规则1:放置一种化学标记物…叫做信息素。规则2:遵循最强的信息素路径。最强的信息素路径有利于蚂蚁寻找食物。
例如,当蚂蚁离开巢穴时,它们会沿着所走的路线留下信息素痕迹。如果它们找到食物,它们会回到同一条路径上的巢穴,信息素的踪迹会变得更强,强度会加倍。根据规则2,因为走较短路径的蚂蚁会首先返回,所以它的信息素轨迹会更强,其他蚂蚁会跟随它。随着越来越多的蚂蚁沿着这条路径行进,信息素的踪迹变得更加强大。
那么,这里发生了什么?每只蚂蚁都遵循两条非常基本的规则,每只蚂蚁都会根据在其直接的局部环境中找到的信息采取行动。重要的是要注意:尽管没有一只蚂蚁知道更大的计划,但它们会集体选择巢穴和食物来源之间的最短路径,因为这是最强化的路径。
顺便说一下,你们中的一些人问过我,我们正在学习的内容与日常生活的相关性。群体智能提供了几个很好的例子,说明了如何将生物学中的概念应用到其他领域。
嗯,企业已经能够在设计复杂系统时使用这种遵循简单规则的方法,例如在电话网络中。当一个电话从一个城市打到另一个城市时,它必须通过沿途的多个节点进行连接。在每一点上,都必须做出决定:电话从这里往哪个方向走?嗯,一个计算机程序被开发出来来回答这个问题,它基于的规则与蚂蚁用来寻找食物的规则相似。记住,单个蚂蚁会沉积信息素,它们会沿着最强化的路径前进。
现在,在电话网络中,计算机监控每条路径的连接速度,并识别当前最快的路径,即网络中最不拥挤的部分。这些信息被转换成数字代码,存储在网络节点上。这加强了目前最不拥挤的道路。电话网络遵循的规则是始终选择最加固的路径。因此,与蚂蚁的行为类似,在每个中间节点上,调用遵循最强化的路径。这将导致对整个网络有利的结果,并且通话速度更快。但回到动物行为上来,群体智能的另一个例子是成群的鸟能够如此紧密地飞行在一起。他们如何协调自己的动作,知道自己应该在哪里?
嗯,基本上可以归结为每只鸟似乎都遵循的三条规则。规则1:靠近附近的鸟类。规则2:避免与附近的鸟类发生碰撞。规则3:以附近鸟类的平均速度和方向移动。
哦,顺便说一句,如果你想知道这种方法如何对人类实用:电影业一直试图在电影场景中创造计算机生成的鸟群。
问题是如何在大规模上轻松做到这一点?一位研究人员在一个计算机图形程序中使用了这三条规则,并且成功了!也有人试图利用这种群体智能的鸟群模型来创造计算机生成的人群。
然而,我并不惊讶需要更多的研究。我提到的三条规则对于鸟类模拟可能很有用,但它们没有考虑到人类行为的复杂性和不可预测性。所以,如果你想以一种真实的方式创造人群,那么这个计算机模型可能太有限了。
三、swarm intelligence 托福听力问题:
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 托福听力答案:
A1:正确答案:C
A2:正确答案:B
A3:正确答案:BD
A4:正确答案:C
A5:正确答案:D
A6:正确答案:A
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