Built Environment Evaluation in Virtual Reality Environments—A Cognitive Neuroscience Approach
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
All in the Mind Psychology for the Curious
All in the Mind Psychology for the Curious Third Edition Adrian Furnham and Dimitrios Tsivrikos www.ebook3000.com This third edition first published 2017 © 2017 John Wiley & Sons, Ltd Edition history: Whurr Publishers Ltd (1e, 1996); Whurr Publishers Ltd (2e, 2001) Registered Office John Wiley & Sons, Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial Offices 350 Main Street, Malden, MA 02148‐5020, USA 9600 Garsington Road, Oxford, OX4 2DQ, UK The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK For details of our global editorial offices, for customer services, and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com/wiley‐blackwell. The right of Adrian Furnham and Dimitrios Tsivrikos to be identified as the authors of this work has been asserted in accordance with the UK Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. -
Concepts As Correlates of Lexical Labels. a Cognitivist Perspective
This is a submitted manuscript version. The publisher should be contacted for permission to re-use or reprint the material in any form. Final published version, copyright Peter Lang: https://doi.org/10.3726/978-3-653-05287-9 Sławomir Wacewicz Concepts as Correlates of Lexical Labels. A Cognitivist Perspective. This is a submitted manuscript version. The publisher should be contacted for permission to re-use or reprint the material in any form. Final published version, copyright Peter Lang: https://doi.org/10.3726/978-3-653-05287-9 CONTENTS Introduction………………………………………………………………... 6 PART I INTERNALISTIC PERSPECTIVE ON LANGUAGE IN COGNITIVE SCIENCE Preliminary remarks………………………………………………………… 17 1. History and profile of Cognitive Science……………………………….. 18 1.1. Introduction…………………………………………………………. 18 1.2. Cognitive Science: definitions and basic assumptions ……………. 19 1.3. Basic tenets of Cognitive 22 Science…………………………………… 1.3.1. Cognition……………………………………………………... 23 1.3.2. Representationism and presentationism…………………….... 25 1.3.3. Naturalism and physical character of mind…………………... 28 1.3.4. Levels of description…………………………………………. 30 1.3.5. Internalism (Individualism) ………………………………….. 31 1.4. History……………………………………………………………... 34 1.4.1. Prehistory…………………………………………………….. 35 1.4.2. Germination…………………………………………………... 36 1.4.3. Beginnings……………………………………………………. 37 1.4.4. Early and classical Cognitive Science………………………… 40 1.4.5. Contemporary Cognitive Science……………………………... 42 1.4.6. Methodological notes on interdisciplinarity………………….. 52 1.5. Summary…………………………………………………………. 59 2. Intrasystemic and extrasystemic principles of concept individuation 60 2.1. Existential status of concepts ……………………………………… 60 2 This is a submitted manuscript version. The publisher should be contacted for permission to re-use or reprint the material in any form. Final published version, copyright Peter Lang: https://doi.org/10.3726/978-3-653-05287-9 2.1.1. -
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. -
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. -
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. -
Pioneers of Computing
Pioneers of Computing В 1980 IEEE Computer Society учредило Золотую медаль (бронзовую) «Вычислительный Пионер» Пионерами учредителями стали 32 члена IEEE Computer Society, связанных с работами по информатике и вычислительным наукам. 1 Pioneers of Computing 1.Howard H. Aiken (Havard Mark I) 2.John V. Atanasoff 3.Charles Babbage (Analytical Engine) 4.John Backus 5.Gordon Bell (Digital) 6.Vannevar Bush 7.Edsger W. Dijkstra 8.John Presper Eckert 9.Douglas C. Engelbart 10.Andrei P. Ershov (theroretical programming) 11.Tommy Flowers (Colossus engineer) 12.Robert W. Floyd 13.Kurt Gödel 14.William R. Hewlett 15.Herman Hollerith 16.Grace M. Hopper 17.Tom Kilburn (Manchester) 2 Pioneers of Computing 1. Donald E. Knuth (TeX) 2. Sergei A. Lebedev 3. Augusta Ada Lovelace 4. Aleksey A.Lyapunov 5. Benoit Mandelbrot 6. John W. Mauchly 7. David Packard 8. Blaise Pascal 9. P. Georg and Edvard Scheutz (Difference Engine, Sweden) 10. C. E. Shannon (information theory) 11. George R. Stibitz 12. Alan M. Turing (Colossus and code-breaking) 13. John von Neumann 14. Maurice V. Wilkes (EDSAC) 15. J.H. Wilkinson (numerical analysis) 16. Freddie C. Williams 17. Niklaus Wirth 18. Stephen Wolfram (Mathematica) 19. Konrad Zuse 3 Pioneers of Computing - 2 Howard H. Aiken (Havard Mark I) – США Создатель первой ЭВМ – 1943 г. Gene M. Amdahl (IBM360 computer architecture, including pipelining, instruction look-ahead, and cache memory) – США (1964 г.) Идеология майнфреймов – система массовой обработки данных John W. Backus (Fortran) – первый язык высокого уровня – 1956 г. 4 Pioneers of Computing - 3 Robert S. Barton For his outstanding contributions in basing the design of computing systems on the hierarchical nature of programs and their data. -
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. -
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. -
Consciousness Is a Thing, Not a Process
applied sciences Opinion Consciousness Is a Thing, Not a Process Susan Pockett School of Psychology, University of Auckland, Auckland, New Zealand; [email protected] Received: 30 October 2017; Accepted: 23 November 2017; Published: 2 December 2017 Featured Application: If the theory outlined here is correct, the construction of artificial consciousness will certainly be possible, but a fundamentally different approach from that currently used in work on artificial intelligence will be necessary. Abstract: The central dogma of cognitive psychology is ‘consciousness is a process, not a thing’. Hence, the main task of cognitive neuroscientists is generally seen as working out what kinds of neural processing are conscious and what kinds are not. I argue here that the central dogma is simply wrong. All neural processing is unconscious. The illusion that some of it is conscious results largely from a failure to separate consciousness per se from a number of unconscious processes that normally accompany it—most particularly focal attention. Conscious sensory experiences are not processes at all. They are things: specifically, spatial electromagnetic (EM) patterns, which are presently generated only by ongoing unconscious processing at certain times and places in the mammalian brain, but which in principle could be generated by hardware rather than wetware. The neurophysiological mechanisms by which putatively conscious EM patterns are generated, the features that may distinguish conscious from unconscious patterns, the general principles that distinguish the conscious patterns of different sensory modalities and the general features that distinguish the conscious patterns of different experiences within any given sensory modality are all described. Suggestions for further development of this paradigm are provided. -
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. -
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. -
Experimente Clasice in Psihologie
PSIHOLOGIE - PSIHOTERAPIE Colecţie coordonată de Simona Reghintovschi DOUGLAS MOOK Experimente clasice în psihologie Traducere din engleză de Clara Ruse Prefaţă la ediţia în limba română de Mihai Aniţei A TRei Editori SILVIU DRAGOMIR VASILE DEM. ZAMFIRESCU Director editorial MAGDALENA MÂRCULESCU Coperta FABER STUDIO (S. OLTEANU, A. RĂDULESCU, D. DUMBRĂVICIAN) Redactor RALUCA HURDUC Director producţie CRISTIAN CLAUDIU COBAN Dtp MARIAN CONSTANTIN Corectori ELENA BIŢU EUGENIA URSU Descrierea CIP a Bibliotecii Naţionale a României MOOK, DOUGLAS Experimente clasice în psihologie / Douglas Mook; trad.: Clara Ruse. - Bucureşti: Editura Trei, 2009 ISBN 978-973-707-286-3 I. Ruse, Clara (trad.) 159.9 Această carte a fost tradusă după Classic Experiments in Psychology de Douglas Mook, Editura Greenwood Press, imprintal Grupului Editorial Greenwood, Westport, CT, U.S.A. (http://www.greenwood.com/greenwood_press.aspx) Copyright © 2004 by Douglas Mook Copyright © Editura Trei, 2009 pentru prezenta ediţie C.P. 27-0490, Bucureşti Tel./Fax: +4 021300 60 90 e-mail: [email protected] www.edituratrei.ro ISBN 978-973-707-286-3 în memoria lui Eliot Stellar, care ar fi -putut o scrie mai bine. Cuprins Prefaţă la ediţia română (de Prof.univ.dr. Mihai Aniţei)................................. 11 Prefaţă .............................................................................................................................. 15 Mulţumiri.........................................................................................................................17