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1969 马文·闵斯基

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Marvin Minsky

PHOTOGRAPHS
BIRTH:
New York City, August 9, 1927

DEATH:
Boston, January 24, 2016

EDUCATION:
Harvard University, B.A. Mathematics (1950); Princeton University, Ph.D. Mathematics (1954)

EXPERIENCE:
United States Navy (1944–45); Junior Fellow, Harvard Society of Fellows (1954–1957); Staff Member, M.I.T. Lincoln Laboratory (1957–1958); Faculty, M.I.T., (from 1959)

HONORS AND AWARDS:
Turing Award, Association for Computing Machinery (1970); Doubleday Lecturer, Smithsonian Institution (1978); Messenger Lecturer, Cornell University (1979); Killian Award, MIT (1989); Japan Prize Laureate (1990); Research Excellence Award, IJCAI (1991); Joseph Priestly Award (1995); Rank Prize, Royal Society of Medicine (1995); IEEE Computer Society Computer  Pioneer Award (1995); Optical Society of America R.W. Wood Prize (2001); Franklin Institute Benjamin Franklin Medal (2001); World Skeptics Congress In Praise of Reason Award (2002); Computer History Museum Fellow (2006); Induction into IEEE Intelligent System's Hall of Fame for "significant contributions to the field of AI and intelligent systems" (2011); Dan David Prize (2014). Past President, American Association for Artificial Intelligence; Fellow, American Academy of Arts and Sciences; Fellow, Institute of Electrical and Electronic Engineers; Fellow, Harvard Society of Fellows; Board of Advisors, Planetary Society; Board of Governors, National Space Society; Member, U.S. National Academy of Engineering; Member, U.S. National Academy of Sciences; Member, Argentine National Academy of Science.


MARVIN MINSKY DL Author Profile link
United States – 1969
CITATION
For his central role in creating, shaping, promoting, and advancing the field of Artificial Intelligence.

SHORT ANNOTATED
BIBLIOGRAPHY
ACM TURING AWARD
LECTURE
RESEARCH
SUBJECTS
ADDITIONAL
MATERIALS
Marvin Minsky is Toshiba Professor of Media Arts and Sciences, Emeritus, and Professor of Electrical Engineering and Computer Science, Emeritus, at the Massachusetts Institute of Technology. His research includes important contributions to cognitive psychology, neural networks, automata theory, symbolic mathematics, and especially artificial intelligence, including work on learning, knowledge representation, common sense reasoning, computer vision, and robot manipulation. He has also made important contributions to graphics and microscope technology.

Minsky was born in New York City. He attended the Fieldston School and the Bronx High School of Science, in New York City, followed by Phillips Academy, in Andover, Massachusetts. After spending time in the United States Navy toward the end of World War II, he continued his education, earning a BA in Mathematics from Harvard College, followed by a PhD in Mathematics from Princeton University.

During his undergraduate years at Harvard, he interacted with the distinguished mathematician Andrew Gleason and the eminent psychologist George Miller. Minsky impressed Gleason with some fixed point theorems in topology, which first established his depth in mathematics and hinted at his eventual elevation to the National Academy of Science.

While at Princeton he built a learning machine, with tubes and motors, which established his passion for building and forecasted his elevation to the National Academy of Engineering. At Princeton, John Tukey and John von Neumann were on his thesis committee.

When he finished his PhD work, John von Neumann, Norbert Wiener, and Claude Shannon supported his admission to the select group of Junior Fellows at Harvard. As a Junior Fellow, Minsky invented the confocal scanning microscope for thick, light-scattering specimens. Light travels from the light source, through a beam splitter, comes to a point inside the specimen, bounces back to the beam splitter, and from there into the viewing optics. Because only one point is viewed at a time, the specimen has to be moved to form a complete image.

Minsky’s invention disappeared from view for many years because the lasers and computer power needed to make it really useful had not yet become available. About ten years after the original patent expired, it started to become a standard tool in biology and materials science.

Minsky’s work on Artificial Intelligence using symbol manipulation dates from the field’s earliest days in the 1950s and 1960s. Many consider his 1960 paper, “Steps toward Artificial Intelligence,” to be the call-to-arms for a generation of researchers. That paper established symbol manipulation—divided into heuristic search, pattern recognition, learning, planning, and induction—to be at the center of any attempt at understanding intelligence.

In the early 1960s, Minsky, along with John McCarthy, founded the MIT Artificial Intelligence Laboratory. Students and staff flocked to this new laboratory to meet the challenge of understanding intelligence and endowing machines with it. Work in the new laboratory included not only attempts to model human perception and intelligence but also efforts to build practical robots. Minsky himself designed and built mechanical hands with tactile sensors and an arm with fourteen-degree-of-freedom. He exploited the fact that the force and torque vector associated with any single point of contact along an arm can be determined by a sophisticated force-sensing wrist.

From the 1960s, Minsky has argued that space exploration, undersea mining, and nuclear safety would be vastly simpler with manipulators driven locally by intelligent computers or remotely by human operators. Early on, he foresaw that microsurgery could be done by surgeons who work at one end of a telepresence system at a comfortably large scale while the other end machines do the chore required at the small scale where tiny nerve bundles are knitted together or clogged blood vessels are reamed out.

In the late 1960s, Minsky began to work on perceptrons, which are simple computational devices that capture some of the characteristics of neural behavior. Minsky and Seymour Papert showed what perceptrons could and could not do, thus raising the sophistication of research on neurally-inspired mechanisms to a new level. Renewed interest in neurally-inspired mechanisms, twenty years later, led to a reprinting of their classic book, Perceptrons [3], with a new chapter treating contemporary developments.

Taken together, Minsky’s steps toward Artificial Intelligence, his early work on symbol manipulation and perceptrons, the founding of the MIT Artificial Intelligence Laboratory, and the work of his earliest students firmly establish Minsky as one of the founders of Artificial Intelligence.

Minsky and Papert continued their collaboration into the 1970s and early 1980s, synergistically bringing together Minsky’s computational ideas with Papert’s understanding of developmental psychology. They worked both together and individually to develop theories of intelligence and radical new approaches to childhood education using Logo, the educational programming language developed by Papert and his colleagues.

Minsky’s best known work from the mid-1970s centers on a family of ideas that he called the Theory of Frames. He emphasized two key concepts in his famous, often reprinted paper, “A Framework for Representing Knowledge.” Minsky’s frames can be summarized by noting two things:


1. objects and situations can be represented as sets of slots and slot-filling values;
2. many slots ordinarily can be filled by inheritance from the default descriptions embedded in a class hierarchy.

A frame describing a birthday party, for example, would have a slot for the person celebrated, the person’s age, the location, and a list of the gifts presented. When published, the Theory of Frames offered not only a fresh way to consider human thinking, but also had high impact on Artificial Intelligence as an emerging engineering discipline: the popular expert-system shells developed during the following decade all offered tools for developing, manipulating, and displaying frames.

A few years later, in “K-lines: A Theory of Memory” (1979), Minsky addressed four key questions:


1. How is information represented?
2. How is it stored?
3. How is it retrieved?
4. How is it used.


His answer was that knowledge lines help us solve a problem by actuating those parts of our brains that put us back in a mental state much like one we were in when we thought about a similar problem before. An elementary physics problem, for example, might take a student into a mental state partially populated with previous applications of Newton’s laws, the conservation of energy, force diagrams, and the role of friction.

In 1985, frames, k-lines and many other ideas came together in Minsky’s book, The Society of Mind [4].  As its name suggests, the book is not about a single idea. Instead it is a statement that intelligence emerges from the cooperative behavior of myriad little agents, no one of which is intelligent by itself. Throughout the book, Minsky presents example after example of these little agents at work, some supporting natural language understanding, some solving problems, others accumulating new ideas, and still others acting as critics.

In 2006, Minsky published a second seminal book, The Emotion Machine [6], which is full of ideas about consciousness, emotions, levels of thinking, and common sense. Multiplicity is a dominant theme. Minsky wrote that our resourceful intelligence arises from many ways of thinking, such as search, analogy, divide and conquer, elevation, reformulation, contradiction, simulation, logical reasoning, and impersonation. These ways of thinking are spread across many levels of mental activity, such as instinctive reactions, learned reactions, deliberative thinking, reflective thinking, self-reflective thinking, and self-conscious emotions. The upper levels of mental activity enable many ways of modeling self, such as physical, emotional, intellectual, professional, spiritual, social, political, economic, and familial. Concepts such as awareness and consciousness seem complex largely because such words do not label single, tightly bounded processes, but rather many different ways of thinking, spread across many levels of mental activity, involving many ways of modeling self; awareness and consciousness are suitcase words so big you can stuff anything into them.

Minsky and his wife, Gloria Rudisch Minsky, have three children, Margaret, Julie, and Henry.



马文-明斯基

照片
出生。
纽约市,1927年8月9日

逝世。
波士顿,2016年1月24日

学历
哈佛大学,数学学士(1950);普林斯顿大学,数学博士(1954)。

经历:美国海军(1944-45)。
美国海军(1944-45);哈佛大学研究员协会初级研究员(1954-1957);麻省理工学院林肯实验室工作人员(1957-1958);麻省理工学院教师(1959年起)

荣誉和奖项。
图灵奖,计算机协会(1970年);Doubleday讲师,史密森学会(1978年);Messenger讲师,康奈尔大学(1979年);Killian奖,麻省理工学院(1989年);日本奖获得者(1990年);卓越研究奖,IJCAI(1991年);Joseph Priestly奖(1995年);Rank奖,皇家医学会(1995年);IEEE计算机学会计算机先锋奖(1995年);美国光学学会R. W. Wood奖(2001年);富兰克林研究所本杰明-富兰克林奖章(2001年);世界怀疑论者大会赞美理性奖(2002年);计算机历史博物馆研究员(2006年);因 "对人工智能和智能系统领域的重大贡献 "而被列入IEEE智能系统名人堂(2011年);丹-大卫奖(2014年)。美国人工智能协会前任主席;美国艺术与科学学院院士;电气与电子工程师协会院士;哈佛大学研究员协会院士;行星协会顾问委员会;国家空间协会理事会;美国国家工程院院士;美国国家科学院院士;阿根廷国家科学院院士。


MARVIN MINSKY DL作者简介链接
美国 - 1969年
嘉奖
因其在创造、塑造、促进和推动人工智能领域的核心作用。

简短注释
书目
亚马逊图灵奖
讲座
研究
主题
额外的
材料
马文-明斯基是麻省理工学院东芝媒体艺术与科学名誉教授,以及电气工程和计算机科学名誉教授。他的研究包括对认知心理学、神经网络、自动机理论、符号数学,特别是人工智能的重要贡献,包括对学习、知识表示、常识推理、计算机视觉和机器人操纵的工作。他还对图形和显微镜技术做出了重要贡献。

明斯基出生在纽约市。他在纽约市的菲尔斯顿学校和布朗克斯科学高中就读,随后在马萨诸塞州安多弗市的菲利普斯学院就读。二战结束时,他在美国海军服役,之后继续接受教育,获得了哈佛学院的数学学士学位,之后又获得了普林斯顿大学的数学博士学位。

在哈佛大学的本科阶段,他与杰出的数学家安德鲁-格里森和著名的心理学家乔治-米勒进行了交流。明斯基用拓扑学中的一些固定点定理给格里森留下了深刻印象,这首次确立了他在数学方面的深度,并暗示了他最终被提升为国家科学院院士。

在普林斯顿时,他建造了一台带有电子管和马达的学习机,这确立了他对建造的热情,并预示着他将被提升到国家工程院。在普林斯顿,约翰-图基和约翰-冯-诺伊曼是他的论文委员会成员。

当他完成他的博士工作时,约翰-冯-诺伊曼、诺伯特-维纳和克劳德-香农支持他进入哈佛大学的初级研究员精选小组。作为初级研究员,明斯基发明了共焦扫描显微镜,用于厚的、光散射的标本。光线从光源出发,经过分光镜,来到标本内的一个点,反弹到分光镜上,然后从那里进入观察光学系统。因为一次只能观察一个点,所以必须移动标本才能形成完整的图像。

明斯基的发明从人们的视线中消失了许多年,因为使其真正有用所需的激光器和计算机功率还没有出现。在最初的专利过期后约十年,它开始成为生物学和材料科学的标准工具。

明斯基利用符号操作进行人工智能的工作可以追溯到20世纪50年代和60年代该领域最早的时期。许多人认为他在1960年发表的论文《迈向人工智能的步骤》是对一代研究者的召唤。那篇论文将符号操作--分为启发式搜索、模式识别、学习、计划和归纳--确立为任何理解智能的尝试的中心。

20世纪60年代初,明斯基与约翰-麦卡锡一起成立了麻省理工学院人工智能实验室。学生和工作人员纷纷涌入这个新的实验室,迎接理解智能和赋予机器智能的挑战。新实验室的工作不仅包括尝试对人类的感知和智能进行建模,还包括努力建造实用的机器人。明斯基自己设计并制造了带有触觉传感器的机械手和一个有14个自由度的手臂。他利用了这样一个事实:与手臂上任何一个接触点相关的力和扭矩矢量都可以由一个复杂的力感应手腕来确定。

从20世纪60年代起,明斯基就认为,如果操纵器由智能计算机在本地驱动或由人类操作员远程驱动,那么太空探索、海底采矿和核安全将大大简化。早期,他预见到显微外科手术可以由外科医生完成,他们在远程呈现系统的一端进行舒适的大规模工作,而另一端的机器则进行小规模的工作,将微小的神经束编织在一起或将堵塞的血管铰出。

在20世纪60年代末,明斯基开始研究感知器,这是一种简单的计算设备,可以捕捉到神经行为的一些特征。明斯基和西摩-帕珀特展示了感知器能做什么和不能做什么,从而将神经启发机制的研究的复杂性提高到一个新的水平。二十年后,人们对神经启发机制的重新关注,导致他们的经典著作《感知器》[3]的再版,其中有一章是关于当代发展的。

综合来看,明斯基迈向人工智能的步伐,他在符号操作和感知器方面的早期工作,麻省理工学院人工智能实验室的成立,以及他最早的学生的工作,都坚定了明斯基作为人工智能的创始人之一的地位。

明斯基和帕珀特的合作一直持续到20世纪70年代和80年代初,将明斯基的计算思想和帕珀特对发展心理学的理解协同起来。他们一起或单独工作,利用帕珀特和他的同事开发的教育编程语言Logo,开发智力理论和儿童教育的激进新方法。

明斯基在20世纪70年代中期最著名的工作集中在他称之为 "框架理论 "的一系列想法上。他在其著名的、经常被重印的论文《代表知识的框架》中强调了两个关键概念。明斯基的框架可以通过注意到两件事来概括。


1.对象和情况可以被表示为槽和填充槽的值的集合。
2.许多槽通常可以通过继承嵌入在类层次结构中的默认描述来填补。

例如,一个描述生日聚会的框架会有一个槽来表示被庆祝的人、这个人的年龄、地点和所送礼物的清单。框架理论发表后,不仅为考虑人类思维提供了一种新的方式,而且对作为新兴工程学科的人工智能产生了很大影响:在接下来的十年中,流行的专家系统外壳都提供了开发、操作和显示框架的工具。

几年后,在《K线。几年后,在 "K线:记忆理论"(1979)中,明斯基解决了四个关键问题。


1. 信息是如何表示的?
2. 2.如何存储?
3. 如何检索?
4. 如何使用它。


他的答案是,知识线通过激活我们大脑的那些部分来帮助我们解决问题,使我们回到与之前思考类似问题时差不多的心理状态。例如,一个初级物理问题可能会把学生带入一个心理状态,其中部分内容是以前对牛顿定律的应用、能量守恒、力图和摩擦力的作用。

1985年,框架、K线和其他许多想法汇集到明斯基的书《心灵的社会》中[4]。 正如它的名字所示,这本书不是关于一个单一的想法。相反,它是一个声明,即智能来自于无数小代理人的合作行为,其中没有一个代理人本身是智能的。在整本书中,明斯基介绍了一个又一个这些小代理工作的例子,有些支持自然语言理解,有些解决问题,有些积累新的想法,还有一些作为批评者。

2006年,明斯基出版了第二本开创性的书《情感机器》[6],其中充满了关于意识、情感、思维层次和常识的想法。多重性是一个主导的主题。明斯基写道,我们足智多谋的智慧产生于许多思维方式,如搜索、类比、分而治之、提升、重新表述、矛盾、模拟、逻辑推理和冒充。这些思维方式分布在许多层次的心理活动中,如本能反应、学习反应、深思熟虑的思维、反思性思维、自我反省的思维和自我意识的情感。心理活动的高层使许多自我建模的方式成为可能,如身体、情感、智力、职业、精神、社会、政治、经济和家庭。意识和意识这样的概念看起来很复杂,主要是因为这样的词并不标示单一的、有严格界限的过程,而是标示许多不同的思维方式,分布在许多层次的心理活动中,涉及许多自我建模的方式;意识和意识是手提箱的词,大到你可以把任何东西塞进去。

明斯基和他的妻子格洛丽亚-鲁迪什-明斯基有三个孩子,玛格丽特、朱莉和亨利。
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