外文翻譯--人工智能

1、<p><b>　　英文原文</b></p><p>　　Artificial Intelligence</p><p>　　Advanced Idea ,Anticipating Incomparability on Artificial Intelligence.</p><p>　　Artificial intelligenc

2、e(AI) is the field of engineering that builds systems ,primarily computer systems ,to perform tasks requiring intelligence .This field of research has often set itself ambitious goals, seeking to build machines that can

3、outlook humans in particular domains of skill and knowledge ,and has achieved some success in this.The key aspects of intelligence around which AI research is usually focused include expert system ,industrial robotics,sy

4、stems and languages language understan</p><p>　　Expert System</p><p>　　An expert system is a set of programs that manipulate encoded knowledge to solve problems in a specialized domain that norm

5、ally requires human expertise . Typically,the user interacts with an expert system in a consultation dialogue,just as he would interact with a human who had some type of expertise,explaining his problem,performing sugges

6、ted tests,and asking questions about proposed solutions. Current experimental systems have achieved high levels of performance in consultation tasks like che</p><p>　?、?Expert systems use knowledge rather th

7、an data to control the solution process.</p><p>　?、?The know is encoded and maintained as an entity separated from</p><p>　　the control program.Furthermore,it is possible in some cases to use di

8、fferent knowledge bases with the same control programs to produce </p><p>　　different types of expert system.Such system are known as expert system</p><p><b>　　shells.</b></p>

9、<p>　　③ Expert systems are capable of explaining how a particular concl-</p><p>　　usion is reached,and why requested information is needed during a consultation.</p><p>　?、?Expert systems

10、use symbolic representations for knowledge and</p><p>　　perform their inference through symbolic computations.</p><p>　?、?Expert systems often reason with metaknowledge.</p><p>　　In

11、dustrial Robotics</p><p>　　An industrial robot is a general-purpose computer-controlled manipulator consisting of several rigid links connected in series by revolute or prismatic joints.Research in this fiel

12、d has looked at everything from the optimal movement of robot arms to methods of planning a sequence of actions to achieve a robot´s goals.Although more complex systems have been built,the thousands of robots that a

13、re being used today in industrial applications are simple devices that have been programmed to some repet</p><p>　?、?Cartesian Robots:A robot whose main frame consist of three Linear axes.</p><p&g

14、t;　?、?Gantry Robots:A Gantry robot is a type of artesian robot whose structure resembles a gantry.This structure is used to minimize deflection along each axis.</p><p>　　③ Cylindrical Robots:A cylindrical ro

15、bot has two linear axes and one rotary axis.</p><p>　　④ Spherical Robots:A spherical robot has one linear axis and two rotary axes.Spherical Robots are used in a variety of industrial tasks such as welding a

16、nd material handling.</p><p>　?、?Articulated Robots:An articulated robot has three rotational axes connecting three rigid links and a base.</p><p>　?、?Scara Robots:One style of robot that has re

17、cently become quite popular is a combination of the articulated arm and the cylindrical robot.The robot has more than three axes and is widely used in electronic assembly.</p><p>　　Systems and Languages</

18、p><p>　　Computer-systems ideas like time-sharing,list processing,and interactive debugging were developed in the AI research environment.Specialized programming languages and systems,with features designed to f

19、acilitate deduction,robot manipulation,cognitive modeling,and so on, have often been rich sources of new ideas.Most recently,reveral knowledge-representation languages,computer languages for encoding knowledge and reason

20、ing methods as data structure and procedures,which have been developed in the </p><p>　　Problem Solving</p><p>　　The first big success in AI was programs that could solve puzzles and play games

21、like chess.Techniques like looking ahead several moves and dividing difficult problems into easier sub-problems evolved into the fundamental AI techniques of search and problem reduction.Today´s programs play champi

22、onship-level checkers and backgammon,as well as very</p><p>　　good chess.Another problem-solving program that integrates mathematical formulates symbolically has attained very high levels of performance and

23、is being used by scientists and engineers.Some programs can even improve their performance with experience.</p><p>　　As discussed above,the open questions in this area involve capabilities that human players

24、 have but cannot articulate,like the chess master´s ability to see the board configuration in terms of meaningful patterns.Another basic open question involves the original conceptualization of a problem,called in A

25、I the choice of problem representation.Humans often solve a problem by finding a way of thinking about it that makes the solution easy-AI problems,so far,must be told how to think about the probl</p><p>　　Lo

26、gical Reasoning</p><p>　　Closely related to problem and puzzle solving was early work on logical deduction.Programs were developed that could prove assertions by manipulating a database of facts,each represe

27、nted by discrete data structures just as they are represented by discrete formulas in mathematical logic.These methods,unlike many other AI techniques,could be shown</p><p>　　to be complete and consistent.Th

28、at is,so long as the original facts were correct,the programs could prove all theorems that followed from the facts,and only those theorems.</p><p>　　Logical reasoning has been one of the most persistently i

29、nvestigated subareas of AI research.Of particular interest are the problems of finding ways of focusing on only the relevant facts of a large database and of keeping track of the justifications for beliefs and updating t

30、hem when new information arrives.</p><p>　　Language Understanding</p><p>　　The domain of language understanding was also investigated by early AI researchers and has consistently attracted inter

31、est.Programs have been written that answer questions posed in English from an internal database,that translate sentences from one language to another,that follow instruction given in English,and that acquire knowledge by

32、 reading textual material and building an internal database.Some programs have even achieved limited success in interpreting instructions spoken into a microphon</p><p><b>　　Learning</b></p>

33、;<p>　　Learning has remained a challenging area for AI.Certainly one of the most salient and significant aspects of human intelligence is the ability to learn.This is a good example of cognitive behavior that is s

34、o poorly understood that vary little progress has been made in achieving it in AI system.There have been several interesting attempts,including programs learn from examples,form their own performance,and from being told.

35、An expert system may perform extensive and costly computations to solve a </p><p>　　Game Playing</p><p>　　Much of the early research in state space search was done using common board games suc

36、h as checkers,chess,and the 15-puzzle.In addition to their inherent intellectual appeal,board games have certain properties that make them ideal subjects for this early work.Most games are played using a well-defined set

37、 of rules,this makes it easy to generate the search space and frees the researcher from many of the ambiguities and complexities inherent in less structured problems.The board configurations use</p><p>　　Con

38、clusion</p><p>　　We have attempted to define artificial intelligence through discussion of its major areas of research and application.In spite of the variety of problems addressed in artificial intelligence

39、 research,a number of important features emerge that seem common to all divisions of the field,these include:</p><p>　?、?The use of computers to do reasoning,learning,or some other form of intelligence.</

40、p><p>　?、?A focus on problems that do not respond to algorithmic solutions.This underlies the reliance on heuristic search as an AI problem-solving technique.</p><p>　　③ Reasoning about the signifi

41、cant qualitative features of a situation.</p><p>　　④ An attempt to deal with issues of semantic meaning as well as syntactic form.</p><p>　?、?The use of large amounts of domain-specific knowledg

42、e in solving problems.This is the basis of expert systems.</p><p><b>　　Abstract</b></p><p>　　Artificial intelligence(AI) is the field of engineering that builds systems,primarily com

43、puter systems,to perform tasks requiring intelligence .This field of research has often set itself ambitious goals,seeking to build machines that can outlook humans in particular domains of skill and knowledge,and has ac

44、hieved some success in this.The key aspects of intelligence around which AI research is usually focused include expert systems,industrial robotics,systems and languages,language understanding</p><p><b>

45、;　　中文譯文</b></p><p><b>　　人工智能</b></p><p>　　先進的想法不斷注入到人工智能的發(fā)展過程中，使其最新理念無與倫比。</p><p>　　人工智能是一個構(gòu)建系統(tǒng)的工程領(lǐng)域，主要用來構(gòu)筑計算機系統(tǒng)，從而完成那些智能化工作。這個研究領(lǐng)域常常樹立野心勃勃的目標，以尋覓來制造出一些擁有人類特定技能和知識

46、的機器，并且已經(jīng)獲得了一些成功的案例。人工智能研究常常聚焦于專家系統(tǒng)，工業(yè)機器人，系統(tǒng)與語言，語言理解，自學(xué)習(xí)，智能游戲等等。</p><p><b>　　專家系統(tǒng)</b></p><p>　　專家系統(tǒng)是這樣一組程序，它們操縱那些表示為代碼的知識來解決一些需要人類專長的某些特定領(lǐng)域的問題。典型地，用戶在向?qū)＜蚁到y(tǒng)請教時，就像是在請教一個有某方面專長的人，這個專家能夠解

47、釋問題，對建議進行檢測，并對解決方案進行質(zhì)疑。在化學(xué)和地址學(xué)的數(shù)據(jù)分析，計算機系統(tǒng)結(jié)構(gòu)，結(jié)構(gòu)工程，甚至在醫(yī)療診斷方面，當(dāng)前實驗性的專家系統(tǒng)都達到了高水平。專家系統(tǒng)可以看作一些專家們的仲裁者，以知識獲取模式工作，而用戶是以請教模式同系統(tǒng)進行交互。并且，在人工智能領(lǐng)域的研究已經(jīng)聚焦于展現(xiàn)系統(tǒng)進行推理的過程，從而讓用戶心悅誠服接受建議，或者幫助用戶專家發(fā)現(xiàn)系統(tǒng)推理時的錯誤。以下是專家系統(tǒng)的特性。</p><p>　?、?/p>

48、專家系統(tǒng)是利用知識而并非數(shù)據(jù)來控制解決進程。</p><p>　　②知識轉(zhuǎn)化成了代碼，并被作為一個區(qū)別于控制程序的實體。而且，在一些情況下將不同的知識運用于同一個控制程序會產(chǎn)生不同類型的專家系統(tǒng)。這些系統(tǒng)被譽為專家系統(tǒng)外殼。</p><p>　?、蹖＜蚁到y(tǒng)有能力解釋一些特定的結(jié)論是如何形成的，并且在推理過程中需要哪些信息。</p><p>　?、軐＜蚁到y(tǒng)利用符號代表

49、知識，并利用符號計算來進行推理論證。</p><p>　?、輰＜蚁到y(tǒng)經(jīng)常利用元知識進行推理。</p><p><b>　　工業(yè)機器人</b></p><p>　　工業(yè)機器人是廣泛使用的由計算機控制的通過外卷的，或棱鏡似的連接結(jié)合起來的操作員。為了達到一個工業(yè)機器人的目標，這個領(lǐng)域的研究集中于設(shè)計一系列的運動來達到最佳的行動方案。雖然工業(yè)機器人需

50、要更復(fù)雜的系統(tǒng)，成千上萬的機器人已經(jīng)應(yīng)用于工業(yè)領(lǐng)域，它們都是一些簡單的經(jīng)過編程的裝置，主要從事一些重復(fù)性工作。機器人和人類相比，工作質(zhì)量好，穩(wěn)定性強，可靠性高。機器人從1965年進入工業(yè)領(lǐng)域，它們具有機械系統(tǒng)的設(shè)計特征。以下是6種公認的工業(yè)機器人結(jié)構(gòu)：</p><p>　?、俚芽▋菏綑C器人：一種主框架由三根直線軸組成的機器人。</p><p>　　②桶架式機器人：桶架式機器人是一種噴水井機

51、器人，它的結(jié)構(gòu)組成了一個桶架。這個結(jié)構(gòu)用來減少每個軸的傾斜度。</p><p>　?、壑鏅C器人：柱面坐標式機器人有兩根直線軸和一個旋轉(zhuǎn)軸。</p><p>　?、芮蚴綑C器人：球式機器人有一根直線軸和兩個旋轉(zhuǎn)軸。球式機器人被應(yīng)用于定位焊接和材料搬運之類的工業(yè)應(yīng)用上。</p><p>　　⑤掛接式機器人：掛接式機器人有三根直線軸連著三個節(jié)點和一個基座。</p&g

52、t;<p>　　⑥斯凱瑞機器人:一種最近變的非常流行的機器人，它是由有關(guān)節(jié)的手臂組成的圓柱體機器人。這種機器人有多于三根的直線軸，并被廣泛應(yīng)用于電子組裝行業(yè)。</p><p><b>　　系統(tǒng)與語言</b></p><p>　　人工智能發(fā)展了計算機系統(tǒng)方面的一些理念，如：時間分配，編目處理，交互式調(diào)試，等等。專用于編程的系統(tǒng)與語言已經(jīng)成為豐富思想的源泉，

53、因為其包含了優(yōu)化演繹，機器人操作，認知模型等等的新特性。特別是最近以來，一些具備知識表示能力的計算機語言已經(jīng)得到進一步的發(fā)展，它們能夠?qū)⒅R轉(zhuǎn)化為代碼，將推理方法表示為數(shù)據(jù)結(jié)構(gòu)。這些計算機語言的發(fā)展已經(jīng)促進了關(guān)于如何構(gòu)建推理機的新思想的萌發(fā)。</p><p><b>　　問題求解</b></p><p>　　人工智能所取得的首次成功是解決了迷宮和棋類游戲的問題。能提前

54、預(yù)料幾步的前瞻技術(shù)和將復(fù)雜問題劃分為容易解決的子問題的技術(shù)已經(jīng)卷入并促進了人工智能中最基本的搜索與問題優(yōu)化技術(shù)的發(fā)展。當(dāng)今的智能程序已經(jīng)能夠在西洋雙陸棋等一些很好的棋類游戲中發(fā)揮世界冠軍級的水平。另外一個整合</p><p>　　數(shù)學(xué)理論的問題求解領(lǐng)域也已經(jīng)達到了很高的水準，并被科學(xué)家和工程師廣泛使用。其中有些程序甚至能夠通過經(jīng)驗積累來不斷提高水平。</p><p>　　像上面所討論的那樣

55、，在此領(lǐng)域都涉及到了人類的本領(lǐng)，但是卻不能進行關(guān)聯(lián)，比如有些老練的棋手有根據(jù)豐富的前景模式通觀全局的本領(lǐng)。另外一個開放式的問題涉及到將一個待求解的問題概念化，在人工智能領(lǐng)域被稱為問題表現(xiàn)的選擇。人類經(jīng)常利用求解問題中簡單的方法來處理問題，因此，人工智能程序，到目前為止，應(yīng)該被告知怎樣去思考它們所要解決的問題。</p><p><b>　　邏輯推理</b></p><p&g

56、t;　　與問題求解密切相關(guān)的是邏輯推斷的早期工作。智能程序不斷的發(fā)展，能夠通過對一個事實數(shù)據(jù)庫的操作來產(chǎn)生斷言，這些斷言由一些不連續(xù)的數(shù)據(jù)結(jié)構(gòu)表示，就像在數(shù)學(xué)邏輯中它們被不連續(xù)的規(guī)則表示一樣。這些方法，不像許多其它的人工智能技術(shù)，能夠展示出是正確的。也就是說，只要原始的事實是正確的，智能程序就能從中證明出所有的定理，同時也只能證明這些定理。</p><p>　　邏輯推理已經(jīng)成為眾多持續(xù)發(fā)展的人工智能子領(lǐng)域之一。其

57、中最令人感興趣的是那些解決問題的方法，它們僅僅聚焦于相關(guān)的事實數(shù)據(jù)庫，并在新的信息發(fā)生時，能夠不斷地檢驗和更新那些信條規(guī)則。</p><p><b>　　語言理解</b></p><p>　　人工智能研究者很早就調(diào)查過語言理解領(lǐng)域，并且此領(lǐng)域極大地激發(fā)了人們的研究興趣。程序可用來解答由內(nèi)部數(shù)據(jù)庫中的英語所提出的問題，可用來將一種語言翻譯為另一種語言，可用來執(zhí)行英語所描

58、述的指令，可用來從文本材料中和所搭建的內(nèi)部數(shù)據(jù)庫中獲取知識。一些智能程序甚至能夠通過語音輸入麥克風(fēng)的方式來代替鍵盤輸入，盡管成功率不是很高。盡管這些語言系統(tǒng)的工作不如從事這些行業(yè)的人們，但是在某些應(yīng)用方面已經(jīng)足夠了。智能程序早期的成功在于能夠回答簡單的詢問和順從簡單的命令，但是早期的機器翻譯是失敗的，這種情況在人工智能對待語言的方式上引發(fā)了徹底的變化。當(dāng)前語言理解方面的研究最基本的主題在于大量基本的、如同常識的世界知識，某些學(xué)科發(fā)展的期

59、待，和在解釋句子時交流的情況，這些都將對語言理解產(chǎn)生重要的影響。</p><p><b>　　自學(xué)習(xí)</b></p><p>　　自學(xué)習(xí)對人工智能而言仍然是一個具有挑戰(zhàn)性的領(lǐng)域。學(xué)習(xí)的本領(lǐng)是人類智能中最顯著和突出的一個方面。這是一種典型的認知行為，但人們卻不太了解它，以至于人工智能在這方面還沒有什么發(fā)展。自學(xué)習(xí)有一些令人感興趣的研究方向，其中包括了從事例中學(xué)習(xí)的智能程

60、序，從自身表現(xiàn)中學(xué)習(xí)的智能程序，從指導(dǎo)中學(xué)習(xí)的智能程序。一個專家系統(tǒng)能夠完成精密復(fù)雜的計算來解決一個問題。往往大多數(shù)專家系統(tǒng)都是隱蔽的，它們蘊涵在其解決問題時所采用的固定不變的策略后面，或在修改大量代碼的難度后面。這些問題最明顯的解決辦法是讓程序能夠自學(xué)習(xí)，或者從經(jīng)驗和分析中學(xué)習(xí)，或者以被告知怎樣做的方式去學(xué)習(xí)。</p><p><b>　　智能游戲</b></p><p

61、>　　一些流傳廣泛的智力游戲，比如國際象棋，西洋雙陸棋，還有走迷宮等等，促進了在狀態(tài)空間探尋的早期研究。這些智力游戲除了與生俱來的智力性的吸引，它們還具備了一些特定的屬性，使其在狀態(tài)空間探尋的早期研究方面成為理想的課題。其中，大多數(shù)游戲在玩的時候都具有一套明確定義的規(guī)則，這個特點使得在游戲時很容易就產(chǎn)生了探尋空間，這樣研究者就從大量含糊的、復(fù)雜的問題中得到解脫。在計算機上進行這些游戲時這些廣闊的狀態(tài)空間是很容易被表示的，一點都不需

62、要復(fù)雜的形式來幫忙。</p><p><b>　　結(jié) 論</b></p><p>　　通過對人工智能主要的研究和應(yīng)用領(lǐng)域的討論，我們嘗試去定義人工智能的概念。盡管人工智能研究中出現(xiàn)了各種各樣的問題，但是在這些各個不同的領(lǐng)域里，都普遍存在大量的重要的特性，其中包括：</p><p>　?、儆嬎銠C進行推理，自學(xué)習(xí)和其它形式的推論。</p>

63、;<p>　?、趩栴}不能反映解決方法，從而成為了焦點。這就構(gòu)成了作為人工智能問題解決技術(shù)的啟發(fā)式搜索的信任度的基礎(chǔ)。</p><p>　　③針對每種情形的顯著特性進行推理。</p><p>　?、芤粋€要解決語義和語法形式之間爭端的意圖。</p><p>　?、菰诮鉀Q問題時采用了大量的專業(yè)領(lǐng)域的知識，這就是專家系統(tǒng)的基礎(chǔ)。</p><