关于人工智能方面的英文论文及其翻译 求关于人工智能方面的英文论文
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Knowing How to Live Alone
Introduction
"Hook"
Connecting Information
Thesis statement
"Alone one is never lonely," says the poet and author Mary Sarton in praise of living along. Most people, however, are terrified of living alone. They are used to living with others -- children with parents, roommates with roommates, friends with friends, husbands with wives. When the statistics catch up with them, therefore, they are rarely prepared. Chances are high that most adult men and women will need to know how to live along, briefly or longer, at some time in their lives.
First Body Paragraph
Topic sentence
Background: Statistics
And how they relate to the thesis.
(The background paragraph is not always included in an academic essay.)
In the United States, circumstances often force people to live alone. For example, many high school and college graduates move away from their hometowns and continue their educations or take jobs. Most schools assign roommates, but employers usually expect people to take care of their own living arrangements. Also, married people might feel they will always be together, but currently one out of two marriages ends in divorce. An even sadder statistic concerns the death of a spouse. Estimates are that in the next twenty years eight out of ten married women will become widows, usually late in life. These facts show that most people have to live by themselves at least once in their lives whether they want to or not.
Second Body Paragraph
Topic sentence
support
One good way to prepare for living alone is to learn how to take care of practical matters. For example, some students and newly single people might not know how to do something as simple as opening a checking account. When making arrangements alone, they might be too tense to find out that they can compare banks as well as the benefits of various types of accounts. Similarly, making major purchases is something people living alone might have to handle. When divorced or widowed people were married, perhaps the other sopuse did the choosing or the couple make the decisions together. But how long can a person manage with a refrigerator that cannot be repaired or a car that will not run? After shopping around and making price comparisons, most people find that these decisions are much less complicated than they seem at first.
Third Body Paragraph
Topic sentence
support
The confidence that single people get from learning to deal with practical matters can boost their chances for establishing new friendships. When singles feel self-reliant, they can have an easier time getting out and meeting new people. For instance, some students are in the habit of always going to classes with a friend. When they break this dependency, they can be pleasantly surprised to find that they can concentrate better on the course and also have a chance to make some new friends. Likewise, the idea of going alone to the beach or to parties can paralyze some singles. Once they make the attempt, however, people alone usually find that almost everyone welcomes a new, friendly face.
Fourth Body Paragraph
Topic sentence
support
Probably the most difficult problem for people living alone is dealing with feelings of loneliness. First, they have to understand the feeling. Some people confuse being alone with feeling lonely. They need to remember that unhappily married people can feel very lonely with spouses, and anyone can suffer from loneliness in a room crowded with friends. Second, people living alone have to fight any tencendies to get depressed. Depression can lead to much unhappiness, including conpulsive behavior like overeating or spending too much money. Depression can also drive people to fill the feeling of emptiness by getting into relationships or jobs that they do not truly want. Third, people living alone need to get involved in useful and pleasurable activities, such as volunteering their services to help others.
Conclusion:
Call for awarness
People need to ask themselves, "If I had to live alone starting tomorrow morning, would I know how?" If the answer is "No," they need to become conscious of what living alone calls for. People who face up to life usually do not have to hide from it later on.
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Artificial Intelligence (AI) is the intelligence of machines and the branch of computer science which aims to create it. Textbooks define the field as "the study and design of intelligent agents,"[1] where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.[2] John McCarthy, who coined the term in 1956,[3] defines it as "the science and engineering of making intelligent machines."[4]The field was founded on the claim that a central property of human beings, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.[5] This raises philosophical issues about the nature of the mind and limits of scientific hubris, issues which have been addressed by myth, fiction and philosophy since antiquity.[6] Artificial intelligence has been the subject of breathtaking optimism,[7] has suffered stunning setbacks[8] and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.[9]
AI research is highly technical and specialized, deeply divided into subfields that often fail to communicate with each other.[10] Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.[11] General intelligence (or "strong AI") is still a long-term goal of (some) research.[12]
Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the golden robots of Hephaestus and Pygmalion's Galatea.[13] Human likenesses believed to have intelligence were built in every major civilization: animated statues were worshipped in Egypt and Greece[14] and humanoid automatons were built by Yan Shi,[15] Hero of Alexandria,[16] Al-Jazari[17] and Wolfgang von Kempelen.[18] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān,[19] Judah Loew[20] and Paracelsus.[21] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots).[22] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods".[6] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.
The problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. The traits described below have received the most attention.[11]
[edit] Deduction, reasoning, problem solving
Early AI researchers developed algorithms that imitated the step-by-step reasoning that human beings use when they solve puzzles, play board games or make logical deductions.[39] By the late 80s and 90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.[40]
For difficult problems, most of these algorithms can require enormous computational resources — most experience a "combinatorial explosion": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. The search for more efficient problem solving algorithms is a high priority for AI research.[41]
Human beings solve most of their problems using fast, intuitive judgments rather than the conscious, step-by-step deduction that early AI research was able to model.[42] AI has made some progress at imitating this kind of "sub-symbolic" problem solving: embodied approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside human and animal brains that gives rise to this skill.
General intelligence
Main articles: Strong AI and AI-complete
Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them.[12] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.[74]
Many of the problems above are considered AI-complete: to solve one problem, you must solve them all. For example, even a straightforward, specific task like machine translation requires that the machine follow the author's argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author's intention (social intelligence). Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it.[75]
[edit] Approaches
There is no established unifying theory or paradigm that guides AI research. Researchers disagree about many issues.[76] A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence, by studying psychology or neurology? Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?[77] Can intelligent behavior be described using simple, elegant principles (such as logic or optimization)? Or does it necessarily require solving a large number of completely unrelated problems?[78] Can intelligence be reproduced using high-level symbols, similar to words and ideas? Or does it require "sub-symbolic" processing?[79]
[edit] Cybernetics and brain simulation
Main articles: Cybernetics and Computational neuroscience
There is no consensus on how closely the brain should be simulated.In the 1940s and 1950s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.[24] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s.
How can one determine if an agent is intelligent? In 1950, Alan Turing proposed a general procedure to test the intelligence of an agent now known as the Turing test. This procedure allows almost all the major problems of artificial intelligence to be tested. However, it is a very difficult challenge and at present all agents fail.
Artificial intelligence can also be evaluated on specific problems such as small problems in chemistry, hand-writing recognition and game-playing. Such tests have been termed subject matter expert Turing tests. Smaller problems provide more achievable goals and there are an ever-increasing number of positive results.
The broad classes of outcome for an AI test are:
Optimal: it is not possible to perform better
Strong super-human: performs better than all humans
Super-human: performs better than most humans
Sub-human: performs worse than most humans
For example, performance at draughts is optimal,[143] performance at chess is super-human and nearing strong super-human,[144] and performance at many everyday tasks performed by humans is sub-human.
A quite different approach is based on measuring machine intelligence through tests which are developed from mathematical definitions of intelligence. Examples of this kind of tests start in the late nineties devising intelligence tests using notions from Kolmogorov Complexity and compression [145] [146]. Similar definitions of machine intelligence have been put forward by Marcus Hutter in his book Universal Artificial Intelligence (Springer 2005), which was further developed by Legg and Hutter [147]. Mathematical definitions have, as one advantage, that they could be applied to nonhuman intelligences and in the absence of human testers.
AI is a common topic in both science fiction and in projections about the future of technology and society. The existence of an artificial intelligence that rivals human intelligence raises difficult ethical issues and the potential power of the technology inspires both hopes and fears.
Mary Shelley's Frankenstein,[160] considers a key issue in the ethics of artificial intelligence: if a machine can be created that has intelligence, could it also feel? If it can feel, does it have the same rights as a human being? The idea also appears in modern science fiction: the film Artificial Intelligence: A.I. considers a machine in the form of a small boy which has been given the ability to feel human emotions, including, tragically, the capacity to suffer. This issue, now known as "robot rights", is currently being considered by, for example, California's Institute for the Future,[161] although many critics believe that the discussion is premature.[162]
Another issue explored by both science fiction writers and futurists is the impact of artificial intelligence on society. In fiction, AI has appeared as a servant (R2D2 in Star Wars), a law enforcer (K.I.T.T. "Knight Rider"), a comrade (Lt. Commander Data in Star Trek), a conqueror (The Matrix), a dictator (With Folded Hands), an exterminator (Terminator, Battlestar Galactica), an extension to human abilities (Ghost in the Shell) and the saviour of the human race (R. Daneel Olivaw in the Foundation Series). Academic sources have considered such consequences as: a decreased demand for human labor,[163] the enhancement of human ability or experience,[164] and a need for redefinition of human identity and basic values.[165]
Several futurists argue that artificial intelligence will transcend the limits of progress and fundamentally transform humanity. Ray Kurzweil has used Moore's law (which describes the relentless exponential improvement in digital technology with uncanny accuracy) to calculate that desktop computers will have the same processing power as human brains by the year 2029, and that by 2045 artificial intelligence will reach a point where it is able to improve itself at a rate that far exceeds anything conceivable in the past, a scenario that science fiction writer Vernor Vinge named the "technological singularity".[164] Edward Fredkin argues that "artificial intelligence is the next stage in evolution,"[166] an idea first proposed by Samuel Butler's "Darwin among the Machines" (1863), and expanded upon by George Dyson in his book of the same name in 1998. Several futurists and science fiction writers have predicted that human beings and machines will merge in the future into cyborgs that are more capable and powerful than either. This idea, called transhumanism, which has roots in Aldous Huxley and Robert Ettinger, is now associated with robot designer Hans Moravec, cyberneticist Kevin Warwick and inventor Ray Kurzweil.[164] Transhumanism has been illustrated in fiction as well, for example in the manga Ghost in the Shell and the science fiction series Dune. Pamela McCorduck writes that these scenarios are expressions of the ancient human desire to, as she calls it, "forge the gods."[6]
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