分析 本文属于演讲稿,作者通过这篇文章向我们介绍了英国的一些法律,让访问英国的 人知道可以做什么不能做什么.
解答 25.B 细节理解题,通读全文可知本文主要是给去英国的旅行者一些建议,故选B.
26.D 细节理解题,根据The first;Secondly;Thirdly;My next point;Finally,可知文章中一共给出了五点建议,故选D.
27.D 细节理解题,根据倒数第二段Finally,it is against the law to buy cigarettes or tobacco (烟草) if you are under 16years old.可知十六岁以下买烟是违法的,故选D.
28.C 细节理解题,根据最后一段I'd like to finish by saying that if you require any sort of help or assistance,you should contact your local police station,who will be pleased to help you.可知如果你需要帮助可以联系当地派出所,故选C.
点评 考查学生的细节理解和推理判断能力.做细节理解题时一定要找到文章中的原句,和题干进行比较,再做出正确选择.在做推理判断题时不要以个人的主观想象代替文章的事实,要根据文章事实进行合乎逻辑的推理判断.
科目:高中英语 来源:2017届河南省新乡市高三第二次模拟测试英语试卷(解析版) 题型:阅读理解
Computers have beaten human world champions at chess and, earlier this year, the board game Go. So far, though, they have struggled at the card table. So we challenged one AI to a game.
Why is poker(扑克)so difficult? Chess and Go are “information complete” games where all players can see all the relevant information. In poker, other players’ cards are hidden, making it an “information incomplete” game. Players have to guess opponents’ hands from their actions----tricky for computers. Poker has become a new benchmark for AI research. Solving poker could lead to many breakthroughs, from cyber security to driverless cars.
Scientists believe it is only a matter of time before AI once again vanquishes humans, hence our human-machine match comes up in a game of Texas Hold’s Em Limit Poker. The AI was developed by Johannes Heinrich, researcher studying machine learning at UCL. It combines two techniques: neural(神经的)networks and reinforcement learning(强化学习).
Neural networks, to some degree, copy the structure of human brains: their processors are highly interconnected and work at the same time to solve problems. They are good at spotting patterns in huge amounts of data. Reinforcement learning is when a machine, given a task, carries it out, learning from mistakes it makes. In this case, it means playing poker against itself billions of times to get better.
Mr Heinrich told Sky News: “Today we are presenting a new procedure that has learned in a different way, more similar to how humans learn. In particular, it is able to learn abstract patterns, represented by its neural network, which allow it to deal with new and unseen situations.”
After two hours of quite defensive play, from the computer at least, we called it a draw.
1.Why can’t the computer beat humans at the poker game?
A. Because humans are cleverer than the computer
B. Because humans practice playing the poker game every day
C. Because the computer can’t know the other players’ cards completely
D. Because the computer can’t learn the regular rules of the poker game
2.What does the underlined word “vanquishes” in Paragraph 3 mean?
A. Leaves B. Defeats C. Cheats D. Serves
3.What do we know about the reinforcement learning of AI?
A. It solves problems correctly every time
B. It is the same as the learning of humans
C. It learns from the mistakes appearing in a task
D. It is more developed than the studying ways of humans
4.What can be inferred from the text?
A. The new procedure of AI has some features of humans
B. Computers are stronger than humans in every aspect
C. Humans will beat computers at playing poker forever
D. Scientists feel unhappy about the result of the poker game
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