1975 艾伦·纽厄尔

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Allen Newell
BIRTH:
March 19, 1927, San Francisco, CA.

DEATH:
July 19, 1992, Pittsburgh, Pennsylvania.

EDUCATION:
BS, Physics (Stanford University, 1949); PhD (Carnegie Institute of Technology, Graduate School of Industrial Administration, 1957.

EXPERIENCE:
US Navy (1943-45); RAND Corporation (1950-1961); Carnegie-Mellon University (1955-1992:graduate student, 1955-57, Professor of Computer Science and Psychology, 1961-1992)

HONORS AND AWARDS:
Harry Goode Memorial Award, American Federation of Information Processing Societies (1971); elected to the United States National Academy of Science. (1972); elected Fellow of the American Academy of Arts and Sciences (1972); A.M. Turing Award of the ACM (1975); Alexander C. Williams Jr. Award (with William C. Biel, Robert Chapman and John L. Kennedy), Human Factors Society (1979); elected to the United States National Academy of Engineering (1980); First President, American Association for Artificial Intelligence (1980); IEEE Computer Society Computer Pioneer Award (1981, charter recipient); Louis E. Levy Medal from the Franklin Institute (1982); Distinguished Scientific Contribution Award, American Psychological Association (1985); Honorary doctorate awarded from University of Pennsylvania (1986); William James Lectures, Harvard University (1987); Award for Research Excellence, International Joint Conference on Artificial Intelligence (1989); Doctor in the Behavioral and Social Sciences (Honorary), University of Gröningen, The Netherlands (1989); William James Fellow Award, American Psychological Society (1989, charter recipient); IEEE Emanuel Piore Award (1990); U.S. National Medal of Science (1992); The ACM/AAAI Allen Newell Award was named in his honor, as well as the Award for Research Excellence of the Carnegie Mellon School of Computer Science.

ALLEN NEWELL DL Author Profile link
United States – 1975
CITATION
In joint scientific efforts extending over twenty years, initially in collaboration with J. C. Shaw at the RAND Corporation, and subsequentially with numerous faculty and student collegues at Carnegie-Mellon University, Newell and co-recipient Herbert A. Simon made basic contributions to artificial intelligence, the psychology of human cognition, and list processing.

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Allen Newell was born in San Francisco on March 19, 1927 to Robert R. Newell, a prominent professor of radiology at Stanford Medical School, and Jeanette La Valley Newell. While Newell did not follow his father into medicine, he admired him greatly, and he certainly inherited his father’s taste for research and his broad intellectual interests. While at Lowell High School in San Francisco, Newell met Noël McKenna; the two married in 1947, when both were 20, and remained married until Newell’s death from cancer in 1992.

Professionally, Newell is chiefly remembered for his important contributions to artificial intelligence research, his use of computer simulations in psychology, and his inexhaustible, infectious energy. His central goal was to understand the cognitive architecture of the human mind and how it enabled humans to solve problems. His remarkable accomplishments in computer science were all means to this end, whether they were the development (with Herbert Simon and J.C. Shaw) of the first list-processing language (IPL) and of programs designed to use heuristics in solving problems (especially the Logic Theorist and General Problem Solver, also developed with Simon and Shaw), or advances in speech recognition and in human-computer interaction. For Newell, the goal was to make the computer into an effective tool for simulating human problem-solving. A computer program that solved a problem in a way that humans did not, or could not, was not terribly interesting to him, even if it solved that problem “better” than humans did. The hope was to develop programs that succeeded at solving problems when and how humans succeeded and failed when and how humans failed.

Newell discusses his driving question: “How can the human mind occur in the physical universe.”       
Newell’s career in science began differently. After a stint in the Navy, during which he assisted his father in mapping radiation distribution after the Bikini Atoll atomic tests, Newell re-enrolled at Stanford, majoring in physics. While at Stanford, he took several courses with George Polya, one of the leading exponents of heuristic problem-solving in mathematics (explained best in Polya’s 1945 book, How to Solve It). The idea of heuristic problem-solving made a great impression on Newell, who realized that humans have neither the time nor the processing power necessary to solve problems using exhaustive algorithmic methods. Rather, humans must use simplified rules—heuristics—to guide selective searches for solutions.

Newell was excited by the power and elegance of mathematics, and in 1949 he left Stanford to begin graduate work in mathematics at Princeton. There Newell worked as a research assistant for Oskar Morgenstern, who had just recently co-authored The Theory of Games and Economic Behavior with John von Neumann, creating the new field of game theory. This stay at Princeton was brief, only one year, and Newell did not become a game theorist or a pure mathematician, but his experiences and contacts there started him on a new path, one that connected the powerful abstractions of formal mathematics with the messy realities of empirical experience.

The first step on this new path was to join John Williams (another Princeton mathematician) in the mathematics division at the newly created RAND Corporation in Santa Monica, CA. At RAND, the Air Force’s “think tank”, Newell’s first work applied game-theoretic methods to organization theory—and organizational reality—resulting in a pair of reports co-authored with Joseph Kruskal. This work led to his involvement with a series of experiments on decision-making in groups being conducted by John L. Kennedy, William Biel, and Robert Chapman at RAND’s Systems Research Center (which was spun off almost a decade later as the Systems Development Corporation).

One of the chief problems in the study of human behavior is the difficulty of creating a true controlled experiment. At the Systems Research Center, Kennedy, Biel, and Chapman sought to create a simulated environment (a model air defense control center) that could be controlled so as to give insight into how people working in this environment interacted with each other, their machines, and with the information presented to them. Newell’s specific task for the group was to use a computer (an IBM Card Programmed Calculator, then quickly becoming a dinosaur in the new age of stored-program machines) to create simulated radar maps. In the process, Newell became fascinated with how people in this environment processed information and made decisions. In addition, experience taught him to think of computers as symbol processors and simulators rather than as big, fast calculators. Symbol processing, decision-making, problem-solving, and simulation thus went together for Newell, leading him to think of minds, computers, experiments, and organizations in new ways.

One of the consultants to the Systems Research Center was Herbert Simon, then a professor at Carnegie Institute of Technology’s new Graduate School of Industrial Administration. Newell and Simon met during Simon’s visit to RAND during the summer of 1952 and immediately discovered that they spoke the same language of symbols, problem-solving, heuristics, and simulations. At the time, they both focused on decision-making in organizations, and Newell saw the computer as a tool for simulating experimental environments, not experimental subjects. It was not until 1954, after attending a seminar at RAND with Oliver Selfridge, that Newell had his “conversion experience,” suddenly seeing the possibilities of using computers to simulate human problem-solving.[1] Indeed, to Newell, the analogy between humans and computing machines was tight: problem-solving was something done by “physical symbol systems,” a category that included both humans and computers as separate species of the same genus.

Newell describes suddenly discovering his life’s central interest: the use of the computer as a model of human cognition.       
After several years of collaboration at a distance (and in person during summers), Newell moved to Pittsburgh to work with Simon at Carnegie Tech in early 1955. While nominally Simon’s PhD student, Newell was in truth an equal partner in their growing research program. The first fruits of their collaboration was the first successful Artificial Intelligence program, the Logic Theorist (LT), completed in late 1955 and first run on a computer in 1956, which was used to prove the theorems of Russell and Whitehead’s Principia Mathematica. In a wonderful twist of irony, Newell and Simon first used Simon’s family to simulate the workings of the Logic Theorist before it was programmed into a computer, so they had people simulate the workings of a machine designed to simulate the workings of people’s minds!

In addition to employing principles of heuristic problem-solving, the Logic Theorist was an error-controlled, feedback “machine” that compared the goal state (the statement to prove) with the current state and performed one of a small set of basic operations in order to reduce the difference between the two states. The Logic Theorist was a remarkable success, and Simon, Newell, and Shaw elaborated on its basic principles in creating another renowned program, The General Problem Solver (GPS) in 1957-1958. The GPS was not quite so universal as its name implied, but it was startlingly good at solving certain kinds of well-defined problems. Even more, GPS, like LT, appeared to solve them in much the same ways that humans did, employing a core method of means-ends analysis that was both simple and general, if not quite universal.

As part of this work on cognitive simulation, Newell, Simon, and Shaw developed the first list-processing language, IPL, which, according to Simon “introduced many ideas that have become fundamental for computer science in general, including lists, associations, schemas (frames), dynamic memory allocation, data types, recursion, associative retrieval, functions as arguments, and generators (streams).”[2] John McCarthy’s LISP, which became the standard language in the AI community after its development in 1958, incorporated these basic principles of IPL in a language with an improved syntax and a “garbage collector” that recovered unused memory.

Newell on the relationship of list processing to his broader career.       
Newell collaborated with Simon for a number of years, but their paths did diverge over time, with Newell working on speech recognition, computer architectures, and human-computer interaction during the late 60s and 70s before turning his focus to his “Soar” project from the 1970s until his death in 1992. The Soar project was Newell’s attempt to develop a unified theory of cognition (a unified theory, not the unified theory, he would note). This unified theory centered on problem-solving, which it described in terms of “production systems” (sets of “if-then” statements), and it incorporated a theory of learning by “chunking” into the problem-solving schema[3]. While the Soar architecture is informed by psychological and neuro-scientific data, it is a structural model of human cognition than does not seek to explain how this structure is realized physically in the brain. The Soar project continues today, long after Newell’s death, fulfilling Newell’s maxim that one should “choose a final project that will outlast you.”



Newell on Soar as a "final project" that would outlast him.       
Newell, like Simon, was an accomplished institution-builder and grant-winner as well as a profound thinker. In these administrative capacities, Newell was instrumental in transforming Carnegie Mellon’s (CMU) Psychology Department into one of the most influential in the United States, in creating CMU’s pioneering School of Computer Science, and in creating CMU’s campus-wide computer network (one of the first in the nation) in 1982.

For all these labors, intellectual and institutional, Newell received a great many honors, including the Harry Goode Award of the American Federation of Information Processing Societies (1971); the A.M. Turing Award of the Association of Computing Machinery (in 1975, with Simon); the Distinguished Scientific Contribution Award of the American Psychological Association (1985); and, just before he died, the National Medal of Science (1992). He was survived by his wife, Noël, his son Paul, and his sister Ann.

For further information on Newell, see the following, especially the pieces by Piccinini and Simon, on which I have drawn heavily for this essay.

Boden. Margaret, Mind as Machine: A History of Cognitive Science, Oxford University Press, 2006.

Laird, John E. and Paul S. Rosenbloom. “The Research of Allen Newell.” AI Magazine, Vol. 13, Num. 4 (1992), pp. 17-45.

Michon, John and Aladin Akyurek, eds. Soar: A Cognitive Architecture in Perspective, Kluwer Academic, Norwell, MA, 1992.

Piccinini, Gualtiero, “Allen Newell.” In the New Dictionary of Scientific Biography, Thomson Gale.

Herbert A. Simon, “Allen Newell: 1927-1992.” IEEE Annals of the History of Computing, Vol. 20, Num. 2 (1998), pp. 63-76.

Steier, David and Tom M. Mitchell, eds. Mind Matters: A Tribute to Allen Newell, Lawrence Eribaum Associates, Mahwah, N.J., 1996.

Author: Hunter Heyck


[1] Simon, Herbert A. “Allen Newell: 1927-1992,” IEEE Annals of the History of Computing, Vol. 20, Num. 2 (1998), pp. 63-76.

[2] Ibid.

[3] Learning by chunking means that when Soar solves a problem, it creates a new production system that links condition to result; the next time Soar has to deal with the same problem, the system follows the link from condition to result without having to solve the problem again.




Allen Newell
诞生。
1927年3月19日，加利福尼亚州旧金山市。

逝世
1992年7月19日，宾夕法尼亚州的匹兹堡。

教育背景。
学士，物理学（斯坦福大学，1949年）；博士（卡内基技术学院，工业管理研究生院，1957年）。

经历。
美国海军（1943-45）；兰德公司（1950-1961）；卡内基-梅隆大学（1955-1992：研究生，1955-57，计算机科学和心理学教授，1961-1992)

荣誉和奖项。
哈利-古德纪念奖，美国信息处理协会联合会（1971）；当选为美国国家科学院院士。(1972年）；当选为美国艺术与科学院院士（1972年）；ACM的A.M. 图灵奖（1975年）；Alexander C. Williams Jr. 威廉姆斯奖（与威廉-C-比尔、罗伯特-查普曼和约翰-L-肯尼迪共同获得），人类因素协会（1979年）；当选为美国国家工程院院士（1980年）；美国人工智能协会第一任主席（1980年）；IEEE计算机协会计算机先锋奖（1981年，特许得主）；路易斯-E。Levy奖章（1982年）；美国心理学会杰出科学贡献奖（1985年）；宾夕法尼亚大学授予荣誉博士学位（1986年）；哈佛大学威廉-詹姆斯讲座（1987年）。国际人工智能联合会议优秀研究奖（1989年）；荷兰格罗宁根大学行为和社会科学博士（荣誉）（1989年）；美国心理学会威廉-詹姆斯研究员奖（1989年，特许获得者）；IEEE伊曼纽尔-皮奥雷奖（1990年）；美国国家科学奖（1992年）。 美国国家科学奖（1992年）；ACM/AAAI艾伦-纽维尔奖是以他的名字命名的，还有卡内基梅隆大学计算机科学学院的卓越研究奖。

ALLEN NEWELL DL作者简介链接
美国 - 1975年
参考文献
在长达20多年的联合科研工作中，最初与兰德公司的J.C.肖合作，随后与卡内基-梅隆大学的众多教师和学生同事合作，纽维尔和共同获奖者赫伯特-A.西蒙对人工智能、人类认知心理学和列表处理做出了基本贡献。

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艾伦-纽维尔于1927年3月19日出生在旧金山，父亲是斯坦福医学院著名的放射学教授罗伯特-R-纽维尔，母亲是珍妮特-拉谷-纽维尔。虽然纽维尔没有跟随他的父亲进入医学界，但他非常钦佩他，而且他当然也继承了他父亲的研究品味和广泛的知识兴趣。在旧金山洛厄尔高中读书时，纽维尔遇到了诺埃尔-麦肯纳；两人于1947年结婚，当时都是20岁，直到1992年纽维尔因癌症去世。

在职业上，纽维尔主要因其对人工智能研究的重要贡献、他在心理学中对计算机模拟的使用，以及他取之不尽、用之不竭的感染力而被人记住。他的中心目标是了解人类思维的认知结构以及它如何使人类解决问题。他在计算机科学方面的杰出成就都是实现这一目标的手段，无论是开发（与赫伯特-西蒙和J.C.肖合作）第一种列表处理语言（IPL）和旨在使用启发式方法解决问题的程序（特别是与西蒙和肖合作开发的逻辑理论家和一般问题解决者），还是语音识别和人机交互方面的进展。对纽维尔来说，其目标是使计算机成为模拟人类解决问题的有效工具。一个计算机程序以人类没有或不能解决的方式来解决一个问题，对他来说并不十分有趣，即使它比人类 "更好 "地解决了这个问题。他希望开发的程序能够在人类成功的时候成功地解决问题，在人类失败的时候失败。

纽维尔讨论了他的驱动问题。"人类的思想如何能在物理宇宙中发生"。       
纽维尔的科学生涯以不同方式开始。在海军服役期间，他协助父亲绘制比基尼环礁原子试验后的辐射分布图，之后纽维尔重新在斯坦福大学注册，主修物理学。在斯坦福大学期间，他跟随乔治-波利亚学习了几门课程，波利亚是数学中启发式问题解决的主要倡导者之一（在波利亚1945年出版的《如何解决》一书中得到了最好的解释）。启发式解决问题的思想给纽维尔留下了深刻的印象，他意识到人类既没有时间也没有必要的处理能力来使用详尽的算法方法解决问题。相反，人类必须使用简化的规则--启发式方法来指导对解决方案的选择性搜索。

纽维尔对数学的力量和优雅感到兴奋，1949年他离开斯坦福大学，开始在普林斯顿大学进行数学研究生学习。在那里，纽维尔担任奥斯卡-摩根斯坦恩的研究助理，后者最近刚刚与约翰-冯-诺伊曼合著了《游戏和经济行为理论》，开创了游戏理论的新领域。在普林斯顿的逗留时间很短，只有一年，纽维尔没有成为博弈理论家或纯数学家，但他在那里的经历和接触使他开始走上一条新的道路，一条将形式数学的强大抽象与经验的混乱现实相联系的道路。

这条新路的第一步是加入约翰-威廉姆斯（另一位普林斯顿的数学家）在加州圣莫尼卡新成立的兰德公司的数学部门工作。在兰德公司，即空军的 "智囊团"，纽维尔的第一项工作是将博弈论方法应用于组织理论和组织现实，结果是与约瑟夫-克鲁斯卡尔共同撰写了两份报告。这项工作导致他参与了由约翰-L-肯尼迪、威廉-比尔和罗伯特-查普曼在兰德公司的系统研究中心（近十年后被剥离为系统开发公司）进行的一系列关于群体决策的实验。

研究人类行为的主要问题之一是难以建立一个真正的受控实验。在系统研究中心，肯尼迪、比尔和查普曼试图创造一个可以控制的模拟环境（一个模型防空控制中心），以便深入了解在这个环境中工作的人是如何相互作用的，他们的机器，以及向他们提供的信息。纽维尔为该小组制定的具体任务是使用一台计算机（IBM卡式编程计算器，当时在存储程序机器的新时代迅速成为一种恐龙）来创建模拟雷达地图。在这个过程中，纽维尔对人们在这种环境中如何处理信息和做出决定着迷了。此外，经验告诉他，要把计算机看作是符号处理器和模拟器，而不是大而快的计算器。因此，符号处理、决策、问题解决和模拟对纽维尔来说是相辅相成的，导致他以新的方式思考思想、计算机、实验和组织。

系统研究中心的顾问之一是赫伯特-西蒙，当时他是卡内基技术学院新成立的工业管理研究生院的教授。纽维尔和西蒙是在1952年夏天西蒙访问兰德公司时认识的，并立即发现他们在符号、问题解决、启发式方法和模拟方面有着相同的语言。当时，他们都专注于组织中的决策，而纽维尔将计算机视为模拟实验环境的工具，而不是实验对象。直到1954年，在与奥利弗-塞尔弗里奇(Oliver Selfridge)一起参加兰德公司的一个研讨会之后，纽维尔才有了他的 "转换经历"，突然看到了用计算机来模拟人类解决问题的可能性。 [1] 事实上，对纽维尔来说，人类和计算机器之间的类比是很紧密的：解决问题是由 "物理符号系统 "完成的，这个类别包括人类和计算机，是同一属的不同物种。

纽维尔描述说，他突然发现了自己一生的核心兴趣：将计算机作为人类认知的模型。       
经过几年的远距离合作（在夏天的时候可以亲自去），纽维尔在1955年初搬到了匹兹堡，与西蒙一起在卡内基理工学院工作。虽然名义上是西蒙的博士生，但纽维尔实际上是他们不断发展的研究项目中的一个平等伙伴。他们合作的第一个成果是第一个成功的人工智能程序--逻辑理论家（LT），该程序于1955年底完成，并于1956年首次在计算机上运行，它被用来证明罗素和怀特海的《数学原理》中的定理。具有讽刺意味的是，纽维尔和西蒙在逻辑理论家被编入计算机之前，首先用西蒙的家人来模拟它的工作原理，因此他们让人们模拟了一台旨在模拟人们思想工作的机器的工作原理!

除了采用启发式解决问题的原则外，逻辑理论家还是一台错误控制的反馈 "机器"，它将目标状态（要证明的语句）与当前状态进行比较，并进行一小部分基本操作，以减少两个状态之间的差异。逻辑理论家》取得了巨大的成功，西蒙、纽维尔和肖在1957-1958年创造了另一个著名的程序--《通用问题解决器》（GPS），对其基本原理进行了阐述。GPS并不像它的名字所暗示的那样具有普遍性，但它在解决某些类型的定义明确的问题方面有惊人的表现。更重要的是，GPS和LT一样，似乎以与人类大致相同的方式来解决这些问题，采用了一种既简单又普遍的手段分析的核心方法，即使不是很普遍。

作为认知模拟工作的一部分，纽维尔、西蒙和肖开发了第一种列表处理语言IPL，根据西蒙的说法，IPL "引入了许多已经成为一般计算机科学基础的想法，包括列表、关联、模式（框架）、动态内存分配、数据类型、递归、关联检索、作为参数的函数和生成器（流）。 "[2] 约翰-麦卡锡的LISP在1958年开发后成为人工智能界的标准语言，它将IPL的这些基本原则纳入到一种语言中，并改进了语法和 "垃圾收集器"，以恢复未使用的内存。

纽维尔关于列表处理与他更广泛的职业生涯的关系。       
纽维尔与西蒙合作了好几年，但他们的道路确实随着时间的推移而分道扬镳，纽维尔在60年代末和70年代从事语音识别、计算机结构和人机交互方面的工作，然后从70年代到1992年去世，他的重点转向他的 "Soar "项目。Soar项目是纽维尔试图发展一种统一的认知理论（他指出，是一种统一的理论，而不是统一的理论）。这个统一的理论以解决问题为中心，用 "生产系统"（"如果-那么 "语句的集合）来描述，并将 "分块 "学习的理论纳入问题解决模式[3]。虽然Soar架构是以心理学和神经科学数据为基础的，但它是一个人类认知的结构模型，并不试图解释这种结构是如何在大脑中物理实现的。Soar项目在纽维尔去世后的今天仍在继续，实现了纽维尔的格言，即一个人应该 "选择一个比你更长久的最终项目"。



纽维尔把 "翱翔 "作为一个将超越他的 "最终项目"。       
纽维尔和西蒙一样，是一个成功的机构建设者和资助者，也是一个深刻的思想家。在这些行政工作中，纽维尔在将卡内基梅隆大学（CMU）的心理学系转变为美国最有影响力的系之一、创建CMU的先锋计算机科学学院以及在1982年创建CMU的全校计算机网络（全美最早的网络之一）方面发挥了作用。

由于所有这些智力和制度上的劳动，纽维尔获得了许多荣誉，包括美国信息处理协会联合会的哈里-古德奖（1971年）；计算机械协会的A.M.图灵奖（1975年，与西蒙一起）；美国心理学协会的杰出科学贡献奖（1985年）；以及就在他去世前，国家科学奖章（1992年）。他的妻子诺埃尔、儿子保罗和妹妹安是他的遗属。

关于纽维尔的进一步信息，请参见以下内容，特别是皮奇尼尼和西蒙的文章，我在这篇文章中大量引用了这些文章。

博登。玛格丽特，《作为机器的心灵》。认知科学的历史》，牛津大学出版社，2006年。

Laird, John E. and Paul S. Rosenbloom. "Allen Newell的研究"。AI杂志，第13卷，第4号（1992年），第17-45页。

Michon, John和Aladin Akyurek, eds. 翱翔。A Cognitive Architecture in Perspective, Kluwer Academic, Norwell, MA, 1992.

Piccinini, Gualtiero, "Allen Newell". 载于《新科学传记词典》，Thomson Gale。

Herbert A. Simon, "Allen Newell: 1927-1992." IEEE计算机历史年鉴，第20卷，第2期（1998年），第63-76页。

Steier, David and Tom M. Mitchell, eds. Mind Matters: A Tribute to Allen Newell, Lawrence Eribaum Associates, Mahwah, N.J., 1996。

作者。亨特-海克


[1] Simon, Herbert A. "Allen Newell: 1927-1992，"IEEE计算机历史年鉴，第20卷，第2期（1998），第63-76页。

[2] 同上。

[3] 分块学习是指，当Soar解决一个问题时，它创建了一个新的生产系统，将条件和结果联系起来；下次Soar要处理同一个问题时，系统会沿着从条件到结果的联系，而不必再次解决这个问题。