W. Brodersen Prof. Michael Dertouzos Lab. Prof. Jerome A. Feldman Dr. Michael Frankel

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W. Brodersen Prof. Michael Dertouzos Lab. Prof. Jerome A. Feldman Dr. Michael Frankel

* DARPA PRINCIPAL INVESTIGATORS MEETING DOUBLETREE INN MONTEREY, CALIFORNIA APRIL 10 - 13, 1983 ATTENDEES ( Dr. Robert Balzer USC-lnformation Sciences Inst. Prof. Robert W. Brodersen DR. BRUCE BUCHANAN Univ. of Calif.-Berkeley STANFORD UNIVERSITY Dr. John H. Cafarella MIT-Lincoln Lab. Prof. Thomas Cheatham Harvard University Aiken Computation Lab. Dr. Danny Cohen USC-lnformation Sciences Inst. Prof. Michael Dertouzos MIT-Computer Science Lab. Prof. Edward A. Feigenbaum Stanford University Prof. Jerome A. Feldman University of Rochester Dr. Michael Frankel SRI International Prof. Robert Gallager MIT-EE and Computer Science Dr. Corded Green Kestrel Institute Dr. Anthony Hearn Rand Corporation Prof. John L Hennessy Stanford University Dr. Estil V. Hoversten Linkabit Corporation "* 2 Prof. Leonard Kleinrock Univ. of Calif.-Los Angeles Prof. Victor R. Lesser University of Massachusetts Dr. Donald Nielson SRI International Prof. Jon McCarthy Stanford University Mr. Alan McLaughlin MIT-Lincoln Lab. Prof. James Meindl Stanford University Prof. Allen Newell Carnegie Mellon University Dr. Nils J. Nilsson SRI International Prof. Allan Oppenheim MIT-EE and Computer Science Prof. Paul Penfield, Jr. Massachusetts Inst, of Technology Dr. Gerald Popek Univ. of Calif. -Los Angeles Dr. Raj D. Reddy Carnegie Mellon University Dr. Daniel R. Ries Computer Corp. of America Prof. Edward R. Riseman Univ. of Massachusetts Prof. Roger C. Shank Yale University \ 3 Prof. Chuck Seitz Calif. Inst, of Technology Prof. Carlo H. Sequin Univ. of Calif.-Berkeley Prof. Joseph F. Traub Columbia University Mr. Keith W. Uncapher USC-lnformation Sciences Inst. Mr. Albert Vezza MIT-Laboratory for Computer Science Mr. David C. Walden Bolt, Beranek and Newman Prof. Patrick Winston MIT-Artificial Intelligence Lab. Dr. Richard Wishner Advanced Information & Decision Systems Dr. William A. Woods Bolt, Beranek and Newman Prof. John M. Wozencraft Naval Postgraduate School Dr. Robert E. Kahn DARPA/IPTO Lt. Col. Duane Adams DARPA/IPTO DR. BARRY LEINER DARPA/IPTO CDR RONALD OHLANDER DARPA/IPTO MR. PAUL LOSLEBEN DARPA/IPTO.

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John Mccarthy
JOHN MCCARTHY: the uncommon logician of common sense Excerpt from Out of their Minds: the lives and discoveries of 15 great computer scientists by Dennis Shasha and Cathy Lazere, Copernicus Press August 23, 2004 If you want the computer to have general intelligence, the outer structure has to be common sense knowledge and reasoning. — John McCarthy When a five-year old receives a plastic toy car, she soon pushes it and beeps the horn. She realizes that she shouldn’t roll it on the dining room table or bounce it on the floor or land it on her little brother’s head. When she returns from school, she expects to find her car in more or less the same place she last put it, because she put it outside her baby brother’s reach. The reasoning is so simple that any five-year old child can understand it, yet most computers can’t. Part of the computer’s problem has to do with its lack of knowledge about day-to-day social conventions that the five-year old has learned from her parents, such as don’t scratch the furniture and don’t injure little brothers. Another part of the problem has to do with a computer’s inability to reason as we do daily, a type of reasoning that’s foreign to conventional logic and therefore to the thinking of the average computer programmer. Conventional logic uses a form of reasoning known as deduction. Deduction permits us to conclude from statements such as “All unemployed actors are waiters, ” and “ Sebastian is an unemployed actor,” the new statement that “Sebastian is a waiter.” The main virtue of deduction is that it is “sound” — if the premises hold, then so will the conclusions.
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The Computer Scientist As Toolsmith—Studies in Interactive Computer Graphics
Frederick P. Brooks, Jr. Fred Brooks is the first recipient of the ACM Allen Newell Award—an honor to be presented annually to an individual whose career contributions have bridged computer science and other disciplines. Brooks was honored for a breadth of career contributions within computer science and engineering and his interdisciplinary contributions to visualization methods for biochemistry. Here, we present his acceptance lecture delivered at SIGGRAPH 94. The Computer Scientist Toolsmithas II t is a special honor to receive an award computer science. Another view of computer science named for Allen Newell. Allen was one of sees it as a discipline focused on problem-solving sys- the fathers of computer science. He was tems, and in this view computer graphics is very near especially important as a visionary and a the center of the discipline. leader in developing artificial intelligence (AI) as a subdiscipline, and in enunciating A Discipline Misnamed a vision for it. When our discipline was newborn, there was the What a man is is more important than what he usual perplexity as to its proper name. We at Chapel Idoes professionally, however, and it is Allen’s hum- Hill, following, I believe, Allen Newell and Herb ble, honorable, and self-giving character that makes it Simon, settled on “computer science” as our depart- a double honor to be a Newell awardee. I am pro- ment’s name. Now, with the benefit of three decades’ foundly grateful to the awards committee. hindsight, I believe that to have been a mistake. If we Rather than talking about one particular research understand why, we will better understand our craft.
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The Dartmouth College Artificial Intelligence Conference: the Next
AI Magazine Volume 27 Number 4 (2006) (© AAAI) Reports continued this earlier work because he became convinced that advances The Dartmouth College could be made with other approaches using computers. Minsky expressed the concern that too many in AI today Artificial Intelligence try to do what is popular and publish only successes. He argued that AI can never be a science until it publishes what fails as well as what succeeds. Conference: Oliver Selfridge highlighted the im- portance of many related areas of re- search before and after the 1956 sum- The Next mer project that helped to propel AI as a field. The development of improved languages and machines was essential. Fifty Years He offered tribute to many early pio- neering activities such as J. C. R. Lick- leiter developing time-sharing, Nat Rochester designing IBM computers, and Frank Rosenblatt working with James Moor perceptrons. Trenchard More was sent to the summer project for two separate weeks by the University of Rochester. Some of the best notes describing the AI project were taken by More, al- though ironically he admitted that he ■ The Dartmouth College Artificial Intelli- Marvin Minsky, Claude Shannon, and never liked the use of “artificial” or gence Conference: The Next 50 Years Nathaniel Rochester for the 1956 “intelligence” as terms for the field. (AI@50) took place July 13–15, 2006. The event, McCarthy wanted, as he ex- Ray Solomonoff said he went to the conference had three objectives: to cele- plained at AI@50, “to nail the flag to brate the Dartmouth Summer Research summer project hoping to convince the mast.” McCarthy is credited for Project, which occurred in 1956; to as- everyone of the importance of ma- coining the phrase “artificial intelli- sess how far AI has progressed; and to chine learning.
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Introduction
INTRODUCTION In which we try to explain why we consider artificial intelligence to be a subject most worthy of study, and in which we try to decide what exactly it is, this being a good thing to decide before embarking. INTELLIGENCE We call ourselves _Homo sapiens—man the wise—because our intelligence is so important to us. For thousands of years, we have tried to understand how we think; that is, how a mere handful of matter can perceive, understand, predict, and manipulate a world far larger and ARTIFICIAL NTIIII GERHIE more complicated than itself. The field of artificial intelligence, or Al, goes further still: it attempts not just to understand but also to build intelligent entities. AI is one of the newest fields in science and engineering. Work started in earnest soon after World War II, and the name itself was coined in 1956. Along with molecular biology, AI is regularly cited as the "field I would most like to be in" by scientists in other disciplines. A student in physics might reasonably feel that all the good ideas have already been taken by Galileo, Newton, Einstein, and the rest. AI, on the other hand, still has openings for several full-time Einsteins and Edisons. Al currently encompasses a huge variety of subfields, ranging from the general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on a crowded street, and diagnosing diseases. AI is relevant to any intellectual task; it is truly a universal field. 1.1 WHAT IS AI? We have claimed that AI is exciting, but we have not said what it is.
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Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration.
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The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm1
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Purdue E-Pubs The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm1 Stellan Ohlssoni Abstract The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon’s most innovative research practices – especially their method for inducing subjects’ strategies from verbal protocols - were abandoned. In this essay, I summarize Newell and Simon’s theoretical and methodological innovations and explain why their strategy identification method did not become a standard research tool. I argue that the method lacked a systematic way to aggregate data, and that Newell and Simon’s search for general problem solving strategies failed. Paradoxically, the theoretical vision that led them to search elsewhere for general principles led researchers away from stud- ’ ies of complex problem solving. Newell and Simon’s main enduring contribution is the theory that people solve problems via heuristic search through a problem space. This theory remains the centerpiece of our understanding of how people solve unfamiliar problems, but it is seriously incomplete. In the early 1970s, Newell and Simon suggested that the field should focus on the question where problem spaces and search strategies come from. I propose a breakdown of this overarching question into five specific research questions. Principled answers to those questions would expand the theory of heuristic search into a more complete theory of human problem solving.
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John W. Mauchly Papers Ms
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Glimm and Witten Receive National Medal of Science, Volume 51, Number 2
Glimm and Witten Receive National Medal of Science On October 22, 2003, President Bush named eight of the nation’s leading scientists and engineers to receive the National Medal of Science. The medal is the nation’s highest honor for achievement in sci- ence, mathematics, and engineering. The medal James G. Glimm Edward Witten also recognizes contributions to innovation, in- dustry, or education. Columbia University in 1959. He is the Distin- Among the awardees are two who work in the guished Leading Professor of Mathematics at the mathematical sciences, JAMES G. GLIMM and EDWARD State University of New York at Stony Brook. WITTEN. Edward Witten James G. Glimm Witten is a world leader in “string theory”, an attempt Glimm has made outstanding contributions to by physicists to describe in one unified way all the shock wave theory, in which mathematical models known forces of nature as well as to understand are developed to explain natural phenomena that nature at the most basic level. Witten’s contributions involve intense compression, such as air pressure while at the Institute for Advanced Study have set in sonic booms, crust displacement in earthquakes, the agenda for many developments, such as progress and density of material in volcanic eruptions and in “dualities”, which suggest that all known string other explosions. Glimm also has been a leading theories are related. theorist in operator algebras, partial differential Witten’s earliest papers produced advances in equations, mathematical physics, applied mathe- quantum chromodynamics (QCD), a theory that matics, and quantum statistical mechanics. describes the interactions among the fundamental Glimm’s work in quantum field theory and particles (quarks and gluons) that make up all statistical mechanics had a major impact on atomic nuclei.
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RAND and the Information Evolution a History in Essays and Vignettes WILLIS H
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