DOCSLIB.ORG

The Seeds of Artificial Intelligence

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The Seeds of Artificial Intelligence U.S. DEPARTMENT OF HEALTH, EDUCATION, and WELFARE The Public Health Service Seeds of National Institutes of Health Artificial Intelligence SUMEX-AIM For Ie lIy tho SupulnLend~nt 01 Doc:um~nU, U.S. Oonmmtnt Prlntlnc omce, Wuhlnclon, D.C. !!Ot02 A publication of The Division of Research Resources National Institutes of Health Seeds of Bethesda, Maryland 20205 Artificial Intelligence Prepared by SUMEX-AIM Research Resources Information Center 1776 East Jefferson Street Rockville, Maryland 20852 under contract N01-RR-9-2114 ; I March 1980 U.S. DEPARTMENT OF HEALTH, EDUCATION, and WELFARE Public Health Service National Institutes of Health NIH Pubicabon No 8G-2071 - This publication was written by Gregory Freiherr I The efforts of many people Acknowledgements made this publication possible. Special thanks go to Mr. Thomas Rindfleisch; Drs. Joshua Leder­ berg, Herbert Simon, Edward Feigenbaum, Bruce Buchanan, Paul Armand, William Baker, Jack Myers. and Harry Pople; and Mr. Edward Post. 3 In the past century, science has the defect of their virtues. They are not only changed our conceptions too detailed, too exhaustive and, Foreword about the world, it has changed it­ most important, too focused on self. Driven by an explosion of in­ Single areas of rapidly expanding formation, specialties in science disciplines. To understand this new have sprung up, inevitably giving branch of computer science, called rise to subspecialties. But staying artificial intelligence (AI) , it is nec­ abreast of new knowledge, even in essary to understand the founda­ narrowly specialized areas, is be­ tion, the broader base, on which it coming increasingly difficult. One rests. way to manage the continuing This publication will present a flood of new information may be to general view of AI , the concepts create entities of intelligence. from which it evolved, its current The proposed tool is the intelli­ abilities, and its promise for re­ gent machine, a device that mimics search. The focus is on a commu­ the expert's reasoning power and nity of projects that use the can retain in retrievable form much SUM EX-AIM (Stanford University of the knowledge currently avail­ Medical Experimental Computer able to experts in a given specialty. for Artificial Intelligence in Medi­ Most systems of this type are still cine) network. immature. But some are already SUMEX-AIM is a nationally moving into the real world and shared computing resource de­ others will make the transition voted entirely to deSigning AI within the next few years. As these applications for the biomedical sci­ activities become more formalized, ences. It is funded by the NIH Divi­ a new branch of applied science sion of Research Resources, will arise. Most likely it will be Biotechnology Resources Pro­ called knowledge engineering. gram. Although SUM EX-AIM does What systems will be available? not include all AI projects directed Who will they help? How will they toward medicine and related re­ work? search in this country, many of the Many answers are contained in programs now using AI techniques existing books and articles. But for medical decision-making were technical publications suffer from developed using this facility. 4 Foreword 4 Table Introduction Artificial Intelligence-What's in a of Name? 6 History of Computing Contents Abacus to EN lAC-and Beyond 9 Processes of Computing The Heuristic Mind 20 SUMEX and the Science Community The Seeds of Artificial Intelligence 24 Biochemistry 25 Clinical Medicine 33 Psychology 54 AI Tool Building 62 Future of AI Prospectus 64 Appendix A Organization and Facilities Available 69 Appendix B Management 71 Appendix C SUM EX-AIM Directory and Project Funding 73 5 For centuries, philosophers and computers are only research tools, linguists have grappled with the machines programmed to do Introduction question of defining intelligence. things that would require intelli­ Most have approached the issue gence if done by people. Dr. Mar­ by describing the function of intelli­ vin L. Minsky, artificial intelligence gence, or the way it appears in be­ (AI) researcher at the Massachu­ havior. An exact definition for this setts Institute of Technology and term is elusive. advisor for SUMEX-AIM, agrees. As might be expected, machine He says artificial intelligence is the intelligence is equally, if not more, science of making machines do difficult to define. According to Dr. things that people need intelli­ Margaret Boden in her book Artiti­ gence to do. ciallntelligence and Natural Man, Others take a somewhat differ- Artificial Intelligence- What's In• a Name? 6 ent view. Dr. Edward Feigenbaum, areas of medical diagnosis and gained from real-world experience. principal investigator of SUMEX­ chemical structure analysis, some When used in AI, heuristics AIM, says the field is not primarily programs can already rival human focus the program's attention on oriented toward technology, but capabilities. Still, many people are those parts of the problem that are toward investigating the nature of skeptical of the computer's poten­ most critical and those parts of the intelligence as information process­ tial. knowledge base that are most rel­ ing, whether the intelligence is ex­ Nobel Prize winner Dr. Herbert evant. The result is that these pro­ pressed by man or machine. A. Simon, psychologist-computer grams pursue a line of reasoning, One point of emphasis in current scientist at Carnegie-Mellon Uni­ rather than a sequence of arith­ AI research is to design computer versity and SUMEX-AIM advisor, is metic steps. programs that capture the knowl­ convinced that this potential is Use of complex symbolic struc­ edge and reasoning processes of generally underrated. He says tures is necessary when construct­ highly intelligent specialists. The human behavior is based on a ing computer applications for practical goal of such work is to complex but definite set of laws. If domains that cannot be well­ make specialized expertise more these laws are discovered and re­ formulated in mathematical terms generally accessible. To do so, duced to computer software, Dr. -either because they are not fully researchers are attempting to Simon believes machine intelli­ understood, as in medical diag­ understand how experts go about gence comparable to man's will nosis, or because the underlying acquiring and using knowledge. become a certainty in specific concepts are intrinsically non­ Principles of how knowledge ac­ areas of expertise. numerical. "Seldom are there crues and how it is retrieved in log­ To capture these higher level equations, in the mathematical ical sequence are extracted. They functions, AI researchers are de­ sense, that relate measurements are then programmed into the veloping a new approach. It IS of body parameters to the diag­ computer. called symbolic computation, a set nosis of disease," says Mr. Within the SUMEX-AIM system, of methods by which abstractions Thomas Rindfleisch, director of the the reasoning processes of physi­ can be expressed and managed in SUMEX computing facility. "Rather, cians, chemists, and other biomed­ the computer to solve non­ the process of diagnosis is charac­ ical scientists are being analyzed. mathematical problems. They em­ terized by a set of strategies hav­ At present, the ability of most pro­ phasize manipulations of symbolic ing to do with rules of experience grams is limited and much less rather than numeric information, and judgmental knowledge. These flexible than the corresponding and they use largely informal or rules govern the interpretation of human intellect. In specialized heuristic decision-making rules observations and guide decisions Dr. Herbert A. Simon, SUMEX-AIM advisor: sorting out the recipe of intelligence. 7 about what other information is come of research such as this at needed to determine the disease SUMEX-AIM is eliciting, organiz­ process involved." ing, and polishing a body of knowl­ For example, INTERNIST, a edge that rarely sees the light of diagnostic computer program in day," he says. "It is the knowledge the SUMEX-AIM network, is fo­ that underlies the expertise of cused on the broadest of medical practice, the knowledge that is specialties-internal medicine. It normally transmitted by a kind of analyzes patient cases by mimick­ osmosis process from master to ing the expert's reasoning process. apprentice. That knowledge will "The method used by physicians to now be codified, taught, used, and arrive at diagnoses requires com­ critiqued." In essence then, a key plex information processing which goal of artificial intelligence re­ bears little resemblance to the search in the SUM EX-AIM com­ statistical manipulations of most munity is to capture in computer computer-based systems," says programs the knowledge and Dr. Jack D. Myers, coprincipal in­ problem-solving abilities of ex­ vestigator of the project at the Uni­ perts. After studying this process in versity of Pittsburgh. "As a result, many specialized areas of exper­ the focus of research in this field of tise, Mr. Rindfleisch says, it may ul­ medical applications has shifted timately be possible to capture in during the past few years from computer programs something of models of statistical inference to the process of creativity and dis­ those using the heuristics of artifi­ covery itself. Programs then would cial intelligence." possess the ability to detect pat­ "In final form, INTERNIST will terns that establish order from amplify intelligence," Dr. Feigen­ chaos, to draw connections be­ baum says. It will supply expert tween seemingly unrelated ideas, advice to the general practitioner and to establish the principles for and physician's assistant, ac­ solutions to new classes of celerating and improving their problems. work. "An equally important out- Dr. Edward Feigenbaum, principal investigator of SUMEX-AIM: "The laws of expertise will be taught, used, and critiqued .• 8 In the millennium before Christ, called it, "the music of the amid the great cities and con­ spheres." He became the first to History quests of Greece and Rome, realize the importance of geomet­ dreamers and theorists were laying ric shape, which governs all nature of the groundwork for today's thinking from crystalline rock to the human machines.
Load more

Recommended publications
  • Comprehensive Bibliography of Machine Learning
    COMPREHENSIVE BIBLIOGRAPHY OF MACHINE LEARNING Paul E. Utgoff Bernard Nudel Rutgers University This chapter consists of a bibliography of the field of machine learning. The sources of the references include bibliographies compiled by Saul Amarel, Dana Angluin, Ryszard S. Michalski, Tom M. Mitchell, Carl Smith, and Bruce G. Buchanan, as well as our own additions. We define fourteen categories to classify the machine learning literature. For each category, there is a list of reference numbers indicating which references belong within that category. In addition, to the left of each reference is a list of category code letters indicating the categories to which the reference belongs. CATEGORIES Category a. Analogy: Investigation of analogical reasoning in problem solving, and the use of analogy as a learning method. {92, 93, 94, 97, 100, 157,274,332,333,374,472,533,563,564, 565} Category b. Background material: General background reading in areas of artifi­ cial intelligence, cognitive science, and related disciplines that lay the framework for many of the machine learning methods. For overviews of work on machine learning in particular, see category o. {3, 4,5, 16,24,29,35,38,40,51,60,61,71,75,84,90, 107, Ill, 119, 129, 131, 132, 142, 148, 149, 153, 158, 160, 161, 166, 170, 171, 175, 176, 179, 180, 185, 205, 234, 237, 239, 252, 261, 270, 289, 292, 294, 320, 329, 330, 331, 334, 355, 358, 359, 362, 363, 369, 374, 391, 392, 393, 396, 397, 398, 400, 403, 413, 416, 429, 430, 441, 447, 448, 450, 463, 464, 467, 473, 486, 513, 523, 524, 525, 526, 544, 545, 546, 547, 559, 568} 512 COMPREHENSIVE BIBLIOGRAPHY OF MACHINE LEARNING Category c.
    [Show full text]
  • In Memoriam: Charles Rosen, Norman Nielsen, and Saul Amarel
    AI Magazine Volume 24 Number 1 (2003) (© AAAI) In Memoriam In Memoriam Charles Rosen, Norman Nielsen, and Saul Amarel Peter E. Hart and Nils J. Nilsson, Ray Perrault, and Tom Mitchell and Casimir A. Kulikowski n the span of a few months, the AI community lost four important figures. The fall of 2002 marked the passing of Ray Reiter, for whom Ia memorial article by Jack Minker appears in this issue. As the issue was going to press, AI lost Saul Amarel, Norm Nielsen, and Charles Rosen. This section of AI Magazine commemorates these friends, lead- ers, and AI pioneers. We thank Tom Mitchell and Casimir Kulikowski for their memorial to Saul Amarel, Ray Perrault for his remembrance of Norm Nielsen, and Peter Hart and Nils Nilsson for their tribute to Charles Rosen. The AI community mourns our lost colleagues and gratefully remembers their contributions, which meant so much to so many and to the advancement of artificial intelligence as a whole. – David Leake 6 AI MAGAZINE Copyright © 2003, American Association for Artificial Intelligence. All rights reserved. 0738-4602-2003 / $2.00 In Memoriam Charles Abraham Rosen, December 7, 1917 – December 8, 2002 SPRING 2003 7 In Memoriam Charles Abraham Rosen— (EBL). These techniques are still foundational to- day, almost 40 years later. Scientist and Visionary: An example of Charlie’s sense of humor is dis- 1917–2002 played in the 1972 SRI film “SHAKEY, the Robot.” Dressed in black cape as a gremlin, Charlie attempts harlie Rosen combined enormous creativity to frustrate SHAKEY by blocking its path to a goal.
    [Show full text]
  • In Memoriam: Charles Rosen, Norman Nielsen, and Saul Amarel
    In Memoriam In Memoriam Charles Rosen, Norman Nielsen, and Saul Amarel Peter E. Hart and Nils J. Nilsson, Ray Perrault, and Tom Mitchell and Casimir A. Kulikowski n the span of a few months, the AI community lost four important figures. The fall of 2002 marked the passing of Ray Reiter, for whom Ia memorial article by Jack Minker appears in this issue. As the issue was going to press, AI lost Saul Amarel, Norm Nielsen, and Charles Rosen. This section of AI Magazine commemorates these friends, lead- ers, and AI pioneers. We thank Tom Mitchell and Casimir Kulikowski for their memorial to Saul Amarel, Ray Perrault for his remembrance of Norm Nielsen, and Peter Hart and Nils Nilsson for their tribute to Charles Rosen. The AI community mourns our lost colleagues and gratefully remembers their contributions, which meant so much to so many and to the advancement of artificial intelligence as a whole. – David Leake 6 AI MAGAZINE Copyright © 2003, American Association for Artificial Intelligence. All rights reserved. 0738-4602-2003 / $2.00 In Memoriam Charles Abraham Rosen, December 7, 1917 – December 8, 2002 SPRING 2003 7 In Memoriam Charles Abraham Rosen— (EBL). These techniques are still foundational to- day, almost 40 years later. Scientist and Visionary: An example of Charlie’s sense of humor is dis- 1917–2002 played in the 1972 SRI film “SHAKEY, the Robot.” Dressed in black cape as a gremlin, Charlie attempts harlie Rosen combined enormous creativity to frustrate SHAKEY by blocking its path to a goal. and a spirit of adventure with an equally (SHAKEY’s planning and execution-monitoring soft- enormous sense of responsibility at all levels.
    [Show full text]
  • Machines Who Think
    Machines Who Think FrontMatter.pmd 1 1/30/2004, 12:15 PM Other books by the author: Familiar Relations (novel) Working to the End (novel) The Fifth Generation (with Edward A. Feigenbaum) The Universal Machine The Rise of the Expert Company (with Edward A. Feigenbaum and H. Penny Nii) Aaron’s Code The Futures of Women (with Nancy Ramsey) FrontMatter.pmd 2 1/30/2004, 12:15 PM Machines Who Think A Personal Inquiry into the History and Prospects of Artificial Intelligence Pamela McCorduck A K Peters, Ltd. Natick, Massachusetts FrontMatter.pmd 3 1/30/2004, 12:15 PM Editorial, Sales, and Customer Service Office A K Peters, Ltd. 63 South Avenue Natick, MA 01760 www.akpeters.com Copyright © 2004 by A K Peters, Ltd. All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilized in any form, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without written permission from the copyright owner. “Artificial Intelligence”. Copyright (c) 1993, 1967, 1963 by Adrienne Rich, from COLLECTED EARLY POEMS: 1950-1970 by Adrienne Rich. Used by permission of W. W. Norton & Company, Inc. Library of Congress Cataloging-in-Publication Data McCorduck, Pamela, 1940- Machines who think : a personal inquiry into the history and prospects of artificial intelligence / Pamela McCorduck.–2nd ed. p. cm. Includes bibliographical references and index. ISBN 1-56881-205-1 1. Artificial intelligence–History. I. Title. Q335.M23 2003 006.3’09–dc21 2003051791 Printed in Canada 08 07 06 05 04 10 9 8 7 6 5 4 3 2 1 FrontMatter.pmd 4 1/30/2004, 12:43 PM To W.J.M., whose energetic curiosity was always a delight and, at the last, a wonder.
    [Show full text]
  • Haym Hirsh Department of Computer Science / Department of Information Science Cornell University Ithaca, NY 14850
    Haym Hirsh Department of Computer Science / Department of Information Science Cornell University Ithaca, NY 14850 Education Ph.D., Computer Science, Stanford University, June 1989 M.S., Computer Science: Artificial Intelligence, Stanford University, June 1985 B.S., Mathematics–Computer Science, University of California, Los Angeles, June 1983 Summa cum laude, Phi Beta Kappa, U.C. Regents Scholar, Departmental Highest Honors, Math/Computer Science Senior Prize Employment History Cornell University, Departments of Computer Science and Information Science - Professor: July 2013–present - Dean, Faculty of Computing and Information Science: July 2013–December 2014 Rutgers University, Department of Computer Science - Department Chair: July 2003–October 2006; July 2012–June 2013 - Professor I: July 2002–June 2013 - Associate Professor: July 1995–June 2002 - Assistant Professor: September 1989–June 1995 Stanford University, Department of Computer Science - Research Assistant/Teaching Assistant/Fellowship Holder: September 1983–June 1989 NASA Ames Research Center, AI Branch - Research Assistant: July–September 1988 University of Southern California, Information Sciences Institute - Research Assistant: March–August 1983 Visiting Positions Massachusetts Institute of Technology, Sloan School of Management - Visiting Scholar: September 2010-August 2011 National Science Foundation, Directorate of Computer and Information Science and Engineering, Division of Information and Intelligent Systems - Director: October 2006-August 2010 University
    [Show full text]
  • Artificial Intelligence Research at Rutgers
    AI Magazine Volume 3 Number 2 (1982) (© AAAI) Research in Progress AI Research at Rutgers Edited by: Tom M. Mitchell Department of Computer Science Rutgers Unaversity New Brunswick, New Jersey 08903 RESEARCH by members of the Department of Computer projects and collaborations with researchers from other in- Science at Rutgers, and by their collaborators, is organized stitutions. The Rutgers Resource is part of the national AliU within the Laboratory for Computer Science Research (LCSR). (AI in Medicine) project which has been supported by NIH AI and AI-related applications are the major area of research since 1974. within LCSR, with about forty people-faculty, staff and graduate students-currently involved in various aspects of More recently, a number of newer AI research projects AI research. have grown within LCSR. Research on AI applications to One project which has had a major impact on the Digital System Design is being conducted under DARPA stimulation and growth of AI research at Rutgers is the Re- sponsorship, with Tom Mitchell and Saul Amarel as Co- search Resource on Computers in Biomedicine, which was Principal Investigators. Research on Al approaches to the started by Saul Amarel in 1971, and has been supported by study of Legal Reasoning is supported by NSF, with Thorne NIH since that time. Casimir Kulikowski is Co-Principal McCarty and N. S. Sridharan as Co-Principal Investigators. Investigator of the Rutgers Research Resource. The em- Research on building AI consultation systems for Naval mis- phasis of research in this project has been on applications sion planning is supported by NRL, with C.
    [Show full text]
  • Strategic Computing : DARPA and the Quest for Machine Intelligence, 1983–1993 / Alex Roland with Philip Shiman
    Strategic Computing History of Computing I. Bernard Cohen and William Aspray, editors William Aspray, John von Neumann and the Origins of Modern Computing Charles J. Bashe, Lyle R. Johnson, John H. Palmer, and Emerson W. Pugh, IBM’s Early Computers Paul E. Ceruzzi, A History of Modern Computing I. Bernard Cohen, Howard Aiken: Portrait of a Computer Pioneer I. Bernard Cohen and Gregory W. Welch, editors, Makin’ Numbers: Howard Aiken and the Computer John Hendry, Innovating for Failure: Government Policy and the Early British Com- puter Industry Michael Lindgren, Glory and Failure: The Difference Engines of Johann Mu¨ller, Charles Babbage, and Georg and Edvard Scheutz David E. Lundstrom, A Few Good Men from Univac R. Moreau, The Computer Comes of Age: The People, the Hardware, and the Software Emerson W. Pugh, Building IBM: Shaping an Industry and Its Technology Emerson W. Pugh, Memories That Shaped an Industry Emerson W. Pugh, Lyle R. Johnson, and John H. Palmer, IBM’s 360 and Early 370 Systems Kent C. Redmond and Thomas M. Smith, From Whirlwind to MITRE: The R&D Story of the SAGE Air Defense Computer Alex Roland with Philip Shiman, Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983–1993 Rau´l Rojas and Ulf Hashagen, editors, The First Computers—History and Architectures Dorothy Stein, Ada: A Life and a Legacy John Vardalas, The Computer Revolution in Canada: Building National Technologi- cal Competence, 1945–1980 Maurice V. Wilkes, Memoirs of a Computer Pioneer Strategic Computing DARPA and the Quest for Machine Intelligence, 1983–1993 Alex Roland with Philip Shiman The MIT Press Cambridge, Massachusetts London, England 2002 Massachusetts Institute of Technology All rights reserved.
    [Show full text]
  • Rutgers, the State University of New Jersey New
    RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY NEW BRUNSWICK AN INTERVIEW WITH GERALD POMPER FOR THE RUTGERS ORAL HISTORY ARCHIVES INTERVIEW CONDUCTED BY SHAUN ILLINGWORTH and GEORGE FAKES and KENNETH CHIH NEW BRUNSWICK, NEW JERSEY APRIL 13, 2016 TRANSCRIPT BY KATHRYN TRACY RIZZI Shaun Illingworth: This begins an interview with Professor Gerald Pomper on April 13, 2016, in New Brunswick, New Jersey, with Shaun Illingworth and … George Fakes: … George Fakes. SI: Thank you very much for being here today. Gerald Pomper: I’m glad to be here. SI: To begin, can you tell us where and when you were born? GP: I was born in New York in the Bronx in 1935, April 2nd. SI: We are now being joined by Kenneth Chee. What were your parents’ names? GP: My father’s name was Moe. My mother’s name was Celia, Celia Cohen. SI: Starting with your father’s side of the family, do you know anything about how they came to the United States? Do you know anything about your grandparents and their families? GP: My parents grew up in a small town in Poland. You can’t even find it on a map, although I did visit it many years ago. They knew each other as kids, but they came to the United States separately. My mother came with her four siblings, my mother. My father followed later. She came right after the end of the First World War. My father came separately in about 1925-‘26. My mother and her family were legal immigrants and went through Ellis Island, which we visited.
    [Show full text]
  • Association for Computing Machinery 2 Penn Plaza, Suite 701, New York
    ACM A N W N A N R N D N S Association for Computing Machinery 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA +1-212-869-7440 www.acm.org Contents N N N ACM Awards Reception and Banquet, June 2017 . .2 Introduction . .3 A.M. Turing Award . .4 ACM Prize in Computing . .5 ACM – AAAI Allen Newell Award . .6 Software System Award . .7 Grace Murray Hopper Award . .8 Paris Kanellakis Theory and Practice Award . .9 Karl V. Karlstrom Outstanding Educator Award . .10 ACM Policy Award . .11 Distinguished Service Award . .12 ACM Athena Lecturer Award . .13 Outstanding Contribution to ACM Award . .14 ACM Presidential Award . .15-17 Doctoral Dissertation Award . .18 ACM Student Research Competition . .19 ACM Fellows . .20 Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics . .21 ACM Gordon Bell Prize . .21 ACM – IEEE CS Eckert-Mauchly Award . .22 ACM – IEEE CS Ken Kennedy Award . .22 ACM – IEEE CS George Michael HPC Memorial Fellowships . .23 SIAM – ACM Prize in Computational Science and Engineering . .23 ACM – CSTA Cutler-Bell Prize . .24 ACM India Doctoral Dissertation Award . .24 ACM China Doctoral Dissertation Award . .25 ACM China Rising Star Award . .25 IPSJ/ACM Award for Early Career Contributions to Global Research . .25 ACM Special Interest Group Awards . .26-27 2017 ACM Award Subcommittee Chairs . .28 ACM Award Nomination Submission Procedures . .29 2018 ACM Award Subcommittee Chairs and Members . .30-31 Past Recipients . .32-36 ACM Fellows . .37-43 In Memoriam, ACM Fellows . .44 1 ACM Awards Reception & Banquet ACM AWARDS N N N N N N The Westin St.
    [Show full text]
  • Academic Computing at Rutgers University. a Case Study. INSTITUTION Human Resources Research Organization,Alexandria, Va
    DOCUMENT RESUME ED 227 829 IR 010 622 AUTHOR Hunter, Beverly TITLE Academic Computing at Rutgers University. A Case Study. INSTITUTION Human Resources Research Organization,Alexandria, Va. SPONS AGENCY National Science Foundation, Washington, D.C. PUB DATE 78 GRANT SED-76-15399 NOTE 86p.; For related documents, see IR 010 619-623. PUB TYPE Reports - Descriptive (141) -- Reports - Research/Technical (143) EDRS PRICE MF01/PC04 Plus Postage. DESCRIPTORS Case Studies; *Computer Assisted Instruction.; Computer Lite-racy; *Computer Oriented Prograts; Computers; *Computer Science Education; *Demonstration Programs; Educational Planning; Higher Education; Program Administration; Program Costs; Program Descriptions; Sdrveys IDENTIFIERS *Rutgers the State University NJ ABSTRACT This case study of academic computing is one of a series focusing,on computers as everydaylearning and teaching tools which is addressed to administritors, teachers,staff, and students who wish to plan or improve the usesotcomputers at theirown institutions: Following a brief description of the purposeand selection of'cases'for the overall study, the reportprofiles academic.computing at Rutgers University, the stateuniversity of New Jersey,-which has 46,000 students enrolled on seven campusesat New Brunswick, Piscataway, Newark, and Camden. Thecomputing history of Rutgers is summarized, covering thkee decadesOrcompute 'sa- The report describes the Center for ComputerandInformatio Services (CCIS), which mangges facilities and support foracademic computing, and student access to computing facilities,including the CCIS, individual academic departments, and computingfacilities provided by the New Jersey Educational Computer Network.Additional sections address costs and budgeting, the spectrum of computerapplications at Rutgers, student accomplishments, computerliteracy, computer science programs, outreach programs(sharing of software, expertise,ind, courses), plans and goals, and lessons learned.
    [Show full text]