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1975 赫伯特·西蒙

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Herbert A. Simon
BIRTH:
June 15, 1916, Milwaukee, Wisconsin, US.

DEATH:
February 9, 2001, Pittsburgh, Pennsylvania, US.

EDUCATION:
BS University of Chicago, Political Science (1937); PhD, University of Chicago, Political Science (1943).

EXPERIENCE:
Assistant Professor of Political Science (later Associate Professor and Department Chair), Illinois Institute of Technology (1944-1949); Professor, Graduate School of Industrial Administration, Carnegie-Mellon University, (1949-1965), Computer Science and Psychology (1965-2001), Trustee for Life (1972-2001)

HONORS AND AWARDS:
A few of Simon’s many prominent awards are: Member, National Academy of Sciences (1972); ACM Turing Award (1975 - with Allen Newell); Nobel Prize in Economics (1978); National Medal of Science (1986); Harold Pender Award (1987); Institute of Operations Research and Management Science von Neumann Theory Prize (1988); APA Lifetime Achievement Award (1993); ACM Fellow (1994); IJCAI Award for Research Excellence (1995); APSA Waldo Award (1995).

HERBERT ("HERB") ALEXANDER SIMON 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, Simon and co-recipient Allen Newell made basic contributions to artificial intelligence, the psychology of human cognition, and list processing.

SHORT ANNOTATED
BIBLIOGRAPHY
ACM TURING AWARD
LECTURE
RESEARCH
SUBJECTS
ADDITIONAL
MATERIALS
Herbert Alexander Simon was born in Milwaukee, Wisconsin on June 15, 1916, to Edna and Arthur Simon. Simon’s father worked for the Cutler-Hammer manufacturing company helping to design control devices. His father’s work was not a direct influence on Simon, but when he later began to study feedback-controlled devices, the connection to his father was a source of pride.

Simon’s family was quite ecumenical regarding religion: Simon himself was raised mostly as a Jew, though he attended a Lutheran Sunday school and later became a Unitarian, in part because there was “no room” in his personal theology for “any notion of a chosen people.” Simon’s highly analytic approach to religion was typical: he applied his own critical, rational faculties to everything—and everyone—he encountered. In particular, he applied it to the human mind and how it solved problems.

The human mind was central to all of Simon’s work, whether in political science, economics, psychology, or computer science. Indeed, to Simon, computer science was psychology by other means. Simon’s remarkable contributions to computer science flowed from his desire to make the computer an effective tool for simulating human problem-solving. To him, a computer program that solved a problem in a way that humans did not (or worse, could not) was not terribly interesting, even if it solved that problem far more efficiently than humans did. Conversely a computer program that failed to solve a problem might be a great achievement, so long as it failed in the ways that humans fail.

One of the most important outcomes of this approach to computer science was Simon’s development—and strong advocacy—of heuristic programming. Drawing on his studies of human psychology and of organizational decision-making, Simon noted that people intend to be rational but that they rarely, if ever, have access to all the information or all the time they would need to make the optimally rational choice. Thus, Simon concluded, we do not, because we cannot, solve problems by using exhaustive, precise algorithms. Rather, we must use simpler heuristics and accept satisfactory rather than optimal results in order to make decisions or solve problems. To use a common analogy: a safecracker with unlimited time can try every combination and thus can be assured of opening the safe eventually. The safecracker who operates in the real world, however, has limited time and so begins by trying combinations based on the owner’s family birthdays, anniversaries, and the like. This heuristic does not guarantee success, but it will work often, and when it works, gives results much more quickly.

Simon and his colleagues Allen Newell and J.C. Shaw employed this notion of heuristic problem-solving in the first successful AI program, the Logic Theorist (LT) of 1955-56, which was used to prove the theorems of Russell and Whitehead’s Principia Mathematica. In a wonderful ironic twist, Simon first used family members to simulate the workings of the Logic Theorist before it was programmed into a computer, so he had people simulate the workings of a machine designed to simulate the workings of people’s minds! Simon was so excited by LT that he famously announced to his undergraduate class the next semester that “Over the Christmas holiday, Allen Newell and I invented a machine that thinks.”

Significantly, 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 1957-8. The GPS was not quite as 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.

Simon’s novel approach to the computer was, in part, a product of his education at the University of Chicago in the 1930s, to which he won admission as an undergraduate by competitive exam. He flourished in the intellectual hothouse of interwar Chicago, attending few courses but reading widely—and debating fiercely—in political science, philosophy, and mathematics. The transition to graduate study at Chicago was nearly seamless for Simon, who relished the demanding, but unstructured, nature of work there in the Department of Political Science.

While at Chicago, Simon encountered the German philosopher, Rudolf Carnap, whose rigorous positivism meshed well with Simon’s emerging outlook. Simon also studied with the pioneering mathematical economist Henry Schultz, who introduced Simon to the burgeoning world of econometrics, to mathematical modeling, to sophisticated work on the theory of measurement, and to the Cowles Commission for Research in Economics, which was home at the time to eleven future Nobel Prize winners in Economics, including Simon. Simon believed that these mathematical economists were developing some powerful tools and techniques for modeling human behavior, but that they had an absurdly unrealistic image of the ability of humans to make rational choices. As he put it, “we need a less God-like, and more rat-like, picture of the chooser.” LT and GPS were intended to create just such “rat-like” models of how people actually solve problems in the real world.

Simon—with a series of collaborators—continued to develop programs designed to simulate the operations of the human information-processing system, ranging from programs that played chess, to the Elementary Perceiver and Memorizer (EPAM, co-created with Edward Feigenbaum) that simulated the processes of human sensory perception and learning, to BACON, which simulated the process of discovery in science. Throughout, he was a strong, even fierce, advocate of the computer program as the best formalism for psychological theories, holding that the program is the theory. The fullest statement of this belief was the monumental text, Human Problem Solving [7], authored by Simon and Newell in 1972, in which they introduced the notion of a program as a set of “production systems”, or “if-then” statements. The flip side of this coin was his insistence that computer simulation was an empirical science that taught us new and valuable things about ourselves and our world; simulation was not an exercise in elaborating tautologies.

Last, but not least, Simon believed that organization and structure were critical. Indeed, what his computer simulations simulated was not the actual physical operations of neurons in the brain, but rather the structure of problem-solving processes. The computer program thus could be a structural model of the mind in action, not a model of its specific physical make-up. Two of the key conclusions he drew about the structure of our human mental processes are that they are hierarchical and that they are associative. In other words, he believed that they have a “tree structure”, with each node/leaf linked to a branch above it. Significantly, to Simon, each “leaf” could either be one thing or a set of things—a list of things, to be precise, with the elements of a list possibly being other leafs with their own lists, and sub-lists. (Think of a “to do” list that contains the item “go grocery shopping”, an item that contains its own sub-list of items to purchase.) Since items on a list could “call” items on other lists, this model of the mind could work associatively within its basic hierarchic structure, creating webs of association amongst the branches of the mind’s tree.

To implement this hierarchical, associative model of the mind, Simon and Newell worked with Shaw (a programmer at RAND) to develop the first list processing language, IPL (Information Processing Language). While IPL, a low-level assembly language for list processing, was largely superseded by John McCarthy’s more powerful high-level list processing language LISP, it was a major influence on the development of later list-processing languages, including LISP itself.

As befits someone fascinated by organizations, Simon was an institution-builder as well as a researcher. In the world of computer science, his most significant institutional legacy is the world-renowned School of Computer Science at Carnegie-Mellon University. Simon, Newell, and their colleague Alan Perlis first created a Department of Computer Science in 1965, and they (and others) expanded it until it became its own school in 1988. In keeping with Simon’s interests in AI, simulation, software design, and human-computer interaction, the Carnegie-Mellon University School of Computer Science excels in those areas.

Simon died on February 9, 2001, having received not only the ACM Turing Award (shared with Newell in 1975), but also the Nobel Prize in Economics (1978), The National Medal of Science (1986), The American Psychological Association’s Lifetime Achievement Award (1993), the American Political Science Association’s Dwight Waldo Award (1995), and the Institute for Operations Research and Management Science Von Neumann Theory Prize (1988). He was survived by his wife of 63 years, Dorothea (who died in August 2002), and their children, Katherine, Peter, and Barbara.

Three useful sources of biographical information on Simon are:

Mie Augier and James March, Models of a Man: essays in honor of Herbert Simon, Cambridge, MA: MIT Press, 2004.
A collection of essays by prominent scholars on Simon’s influence on them and their fields.
Hunter Crowther-Heyck, Herbert A. Simon: the bounds of reason in modern America, Baltimore, MD: Johns Hopkins University Press, 2005.
The standard intellectual biography of Simon.
Herbert Simon, Models of My Life, NY: Basic Books, 1991.
Simon’s own autobiography.
Author: Hunter Heyck



赫伯特-A-西蒙
出生地:美国威斯康星州密尔沃基
1916年6月15日,美国威斯康星州密尔沃基市。

逝世
2001年2月9日,美国宾夕法尼亚州的匹兹堡。

教育背景:芝加哥大学政治学学士。
芝加哥大学政治学学士(1937);芝加哥大学政治学博士(1943)。

工作经历:政治学助理教授(后为副教授)。
伊利诺伊理工学院政治学助理教授(后为副教授和系主任)(1944-1949);卡内基-梅隆大学工业管理研究生院教授(1949-1965),计算机科学和心理学(1965-2001),终身理事(1972-2001)。

荣誉和奖项。
西蒙的众多知名奖项中的几个是 美国国家科学院院士(1972年);ACM图灵奖(1975年-与艾伦-纽维尔一起);诺贝尔经济学奖(1978年);国家科学奖(1986年);哈罗德-彭德奖(1987年);运筹学和管理科学研究所冯-诺伊曼理论奖(1988年);APA终身成就奖(1993年);ACM研究员(1994年);IJCAI优秀研究奖(1995年);APSA沃尔多奖(1995)。

HERBERT ("HERB") ALEXANDER SIMON DL作者简介链接
美国 - 1975年
参考文献
在长达20多年的联合科学努力中,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,西蒙和共同获奖者艾伦-纽维尔对人工智能、人类认知心理学和列表处理做出了基本贡献。

简短注释的
书目
亚马逊图灵奖
讲座
研究
主题
额外的
材料
赫伯特-亚历山大-西蒙于1916年6月15日出生在威斯康星州的密尔沃基,父亲是埃德纳和阿瑟-西蒙。西蒙的父亲为卡特勒-哈默制造公司工作,帮助设计控制设备。他父亲的工作对西蒙没有直接影响,但当他后来开始研究反馈控制设备时,与他父亲的联系是他的一个骄傲。

西蒙的家庭在宗教方面是相当大公无私的。西蒙本人主要是作为犹太人长大的,尽管他参加了路德教的主日学,后来成为一元论者,部分原因是在他的个人神学中 "没有空间 "容纳 "任何选民的概念"。西蒙对宗教的高度分析方法是典型的:他将自己的批判性、理性能力应用于他遇到的每一件事--而且是每一个人。特别是,他把它应用于人类的思想以及它如何解决问题。

无论是在政治学、经济学、心理学还是计算机科学方面,人类的思想都是西蒙所有工作的核心。事实上,对西蒙来说,计算机科学就是通过其他方式的心理学。西蒙对计算机科学的杰出贡献来自于他想让计算机成为模拟人类解决问题的有效工具的愿望。对他来说,一个计算机程序以人类没有(或更糟糕的是,不能)解决的问题并不十分有趣,即使它解决该问题的效率远高于人类。相反,一个未能解决问题的计算机程序可能是一个伟大的成就,只要它以人类失败的方式失败。

这种计算机科学方法的最重要的成果之一是西蒙对启发式编程的发展和大力倡导。根据他对人类心理学和组织决策的研究,西蒙指出,人们希望自己是理性的,但他们很少,如果有的话,能够获得所有的信息或所有的时间来做出最合理的选择。因此,西蒙总结说,我们不会,因为我们不能,通过使用详尽的、精确的算法来解决问题。相反,我们必须使用更简单的启发式方法,并接受令人满意而非最佳的结果,以便做出决定或解决问题。用一个常见的比喻:一个拥有无限时间的保险箱盗窃者可以尝试每一种组合,因此可以保证最终打开保险箱。然而,在现实世界中操作的保险箱盗窃者的时间是有限的,所以一开始就根据主人的家庭生日、纪念日等来尝试各种组合。这种启发式方法并不能保证成功,但它经常会奏效,而且一旦奏效,就能更快地得到结果。

西蒙和他的同事艾伦-纽维尔和J.C.肖在第一个成功的人工智能程序中采用了这种启发式解决问题的概念,即1955-56年的逻辑理论家(LT),它被用来证明罗素和怀特海的《数学原理》中的定理。一个奇妙的讽刺性转折是,在逻辑理论家被编入计算机之前,西蒙首先利用家庭成员来模拟其工作原理,因此他让人们模拟了一台旨在模拟人们思维工作原理的机器的工作原理! 西蒙对LT感到非常兴奋,以至于他在下个学期向他的本科班级宣布:"在圣诞节假期,艾伦-纽维尔和我发明了一台会思考的机器。"

重要的是,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(要证明的声明)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年至1958年创造了另一个著名的程序 "一般问题解决者"(GPS),对其基本原则进行了阐述。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,似乎是以与人类相同的方式来解决这些问题。

西蒙对计算机的新方法在某种程度上是他在20世纪30年代在芝加哥大学接受教育的产物,他通过竞争性考试获得了该大学的本科录取。他在战时芝加哥的知识温室中茁壮成长,参加的课程不多,但在政治学、哲学和数学方面进行了广泛的阅读和激烈的辩论。对西蒙来说,在芝加哥的研究生学习的过渡几乎是无缝的,他很喜欢政治学系的工作,要求很高,但没有结构化的性质。

在芝加哥时,西蒙遇到了德国哲学家鲁道夫-卡尔纳普,他的严谨实证主义与西蒙的新兴观点相吻合。西蒙还与先锋数学经济学家亨利-舒尔茨一起学习,他将西蒙引入了新兴的计量经济学世界、数学建模、复杂的测量理论工作,以及考尔斯经济学研究委员会,该委员会当时有11位未来的诺贝尔经济学奖得主,包括西蒙。西蒙认为,这些数学经济学家正在开发一些强大的工具和技术来模拟人类行为,但他们对人类做出理性选择的能力有一个荒谬的不现实的印象。正如他所说,"我们需要一个不那么像上帝,而更像老鼠的选择者形象"。LT和GPS的目的就是要建立这样的 "老鼠式 "模型,说明人们在现实世界中是如何解决问题的。

西蒙与一系列合作者继续开发旨在模拟人类信息处理系统运作的程序,从下棋的程序,到模拟人类感官知觉和学习过程的基本感知器和记忆器(EPAM,与爱德华-费根鲍姆共同创建),再到模拟科学发现过程的BACON。自始至终,他都是计算机程序作为心理学理论的最佳形式主义的强烈甚至是激烈的倡导者,认为程序就是理论。对这一信念最充分的表述是1972年由西蒙和纽维尔撰写的巨著《人类问题解决》[7],其中他们提出了程序是一组 "生产系统 "或 "if-then "语句的概念。这枚硬币的另一面是,他坚持认为计算机模拟是一门实证科学,它能教会我们关于我们自己和我们的世界的新的和有价值的东西;模拟不是一种阐述同义反复的练习。

最后,但同样重要的是,西蒙认为组织和结构是至关重要的。事实上,他的计算机模拟所模拟的不是大脑中神经元的实际物理运作,而是解决问题的过程的结构。因此,计算机程序可以是行动中的思维的结构模型,而不是其具体物理构成的模型。他对我们人类心理过程的结构得出的两个关键结论是:它们是分层的,它们是联想的。换句话说,他认为它们有一个 "树状结构",每个节点/叶子都与它上面的一个分支相连。重要的是,对西蒙来说,每片 "叶子 "既可以是一件事,也可以是一组事--准确地说,是一组事的列表,列表的元素可能是其他叶子,有它们自己的列表和子列表。(想想一个包含 "去买菜 "项目的 "待办事项 "清单,这个项目包含它自己的待购物品的子清单)。由于清单上的项目可以 "调用 "其他清单上的项目,这种心智模型可以在其基本的层次结构中进行关联工作,在心智树的各个分支之间建立关联网。

为了实现这种分层的、联想式的思维模型,西蒙和纽维尔与肖(兰德公司的一名程序员)合作开发了第一种列表处理语言,IPL(信息处理语言)。虽然IPL是一种用于列表处理的低级汇编语言,在很大程度上被约翰-麦卡锡更强大的高级列表处理语言LISP所取代,但它对后来的列表处理语言,包括LISP本身的发展有很大影响。

与对组织着迷的人一样,西蒙是一个机构的建立者,也是一个研究者。在计算机科学领域,他最重要的机构遗产是卡内基-梅隆大学的世界知名的计算机科学学院。西蒙、纽维尔和他们的同事艾伦-珀利斯于1965年首次创建了计算机科学系,他们(和其他人)将其扩大,直到1988年成为自己的学院。与西蒙在人工智能、模拟、软件设计和人机交互方面的兴趣相一致,卡内基-梅隆大学计算机科学学院在这些领域表现出色。

西蒙于2001年2月9日去世,他不仅获得了ACM图灵奖(1975年与纽维尔共享),还获得了诺贝尔经济学奖(1978年)、国家科学奖章(1986年)、美国心理学会终身成就奖(1993年)、美国政治学会德怀特-沃尔多奖(1995年),以及运筹学和管理科学研究所冯诺伊曼理论奖(1988年)。他有63年的妻子多萝西娅(2002年8月去世),以及他们的孩子凯瑟琳、彼得和巴巴拉。

关于西蒙的传记资料,有三个有用的来源。

Mie Augier和James March, Models of a Man: essays in honor of Herbert Simon, Cambridge, MA: 麻省理工学院出版社,2004年。
一本由知名学者撰写的关于西蒙对他们和他们的领域的影响的论文集。
Hunter Crowther-Heyck, Herbert A. Simon: the bounds of reason in modern America, Baltimore, MD: Johns Hopkins University Press, 2005.
西蒙的标准智力传记。
Herbert Simon, Models of My Life, NY: Basic Books, 1991.
西蒙自己的自传。
作者。亨特-海克
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