Yale College Programs of Study 2014–2015
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Artificial Consciousness and the Consciousness-Attention Dissociation
Consciousness and Cognition 45 (2016) 210–225 Contents lists available at ScienceDirect Consciousness and Cognition journal homepage: www.elsevier.com/locate/concog Review article Artificial consciousness and the consciousness-attention dissociation ⇑ Harry Haroutioun Haladjian a, , Carlos Montemayor b a Laboratoire Psychologie de la Perception, CNRS (UMR 8242), Université Paris Descartes, Centre Biomédical des Saints-Pères, 45 rue des Saints-Pères, 75006 Paris, France b San Francisco State University, Philosophy Department, 1600 Holloway Avenue, San Francisco, CA 94132 USA article info abstract Article history: Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to Received 6 July 2016 implement sophisticated forms of human intelligence in machines. This research attempts Accepted 12 August 2016 to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable Keywords: once we overcome short-term engineering challenges. We believe, however, that phenom- Artificial intelligence enal consciousness cannot be implemented in machines. This becomes clear when consid- Artificial consciousness ering emotions and examining the dissociation between consciousness and attention in Consciousness Visual attention humans. While we may be able to program ethical behavior based on rules and machine Phenomenology learning, we will never be able to reproduce emotions or empathy by programming such Emotions control systems—these will be merely simulations. Arguments in favor of this claim include Empathy considerations about evolution, the neuropsychological aspects of emotions, and the disso- ciation between attention and consciousness found in humans. -
Computability and Complexity
Computability and Complexity Lecture Notes Herbert Jaeger, Jacobs University Bremen Version history Jan 30, 2018: created as copy of CC lecture notes of Spring 2017 Feb 16, 2018: cleaned up font conversion hickups up to Section 5 Feb 23, 2018: cleaned up font conversion hickups up to Section 6 Mar 15, 2018: cleaned up font conversion hickups up to Section 7 Apr 5, 2018: cleaned up font conversion hickups up to the end of these lecture notes 1 1 Introduction 1.1 Motivation This lecture will introduce you to the theory of computation and the theory of computational complexity. The theory of computation offers full answers to the questions, • what problems can in principle be solved by computer programs? • what functions can in principle be computed by computer programs? • what formal languages can in principle be decided by computer programs? Full answers to these questions have been found in the last 70 years or so, and we will learn about them. (And it turns out that these questions are all the same question). The theory of computation is well-established, transparent, and basically simple (you might disagree at first). The theory of complexity offers many insights to questions like • for a given problem / function / language that has to be solved / computed / decided by a computer program, how long does the fastest program actually run? • how much memory space has to be used at least? • can you speed up computations by using different computer architectures or different programming approaches? The theory of complexity is historically younger than the theory of computation – the first surge of results came in the 60ties of last century. -
Inventing Computational Rhetoric
INVENTING COMPUTATIONAL RHETORIC By Michael W. Wojcik A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Digital Rhetoric and Professional Writing — Master of Arts 2013 ABSTRACT INVENTING COMPUTATIONAL RHETORIC by Michael W. Wojcik Many disciplines in the humanities are developing “computational” branches which make use of information technology to process large amounts of data algorithmically. The field of computational rhetoric is in its infancy, but we are already seeing interesting results from applying the ideas and goals of rhetoric to text processing and related areas. After considering what computational rhetoric might be, three approaches to inventing computational rhetorics are presented: a structural schema, a review of extant work, and a theoretical exploration. Copyright by MICHAEL W. WOJCIK 2013 For Malea iv ACKNOWLEDGEMENTS Above all else I must thank my beloved wife, Malea Powell, without whose prompting this thesis would have remained forever incomplete. I am also grateful for the presence in my life of my terrific stepdaughter, Audrey Swartz, and wonderful granddaughter Lucille. My thesis committee, Dean Rehberger, Bill Hart-Davidson, and John Monberg, pro- vided me with generous guidance and inspiration. Other faculty members at Michigan State who helped me explore relevant ideas include Rochelle Harris, Mike McLeod, Joyce Chai, Danielle Devoss, and Bump Halbritter. My previous academic program at Miami University did not result in a degree, but faculty there also contributed greatly to my the- oretical understanding, particularly Susan Morgan, Mary-Jean Corbett, Brit Harwood, J. Edgar Tidwell, Lori Merish, Vicki Smith, Alice Adams, Fran Dolan, and Keith Tuma. -
Computability Theory
CSC 438F/2404F Notes (S. Cook and T. Pitassi) Fall, 2019 Computability Theory This section is partly inspired by the material in \A Course in Mathematical Logic" by Bell and Machover, Chap 6, sections 1-10. Other references: \Introduction to the theory of computation" by Michael Sipser, and \Com- putability, Complexity, and Languages" by M. Davis and E. Weyuker. Our first goal is to give a formal definition for what it means for a function on N to be com- putable by an algorithm. Historically the first convincing such definition was given by Alan Turing in 1936, in his paper which introduced what we now call Turing machines. Slightly before Turing, Alonzo Church gave a definition based on his lambda calculus. About the same time G¨odel,Herbrand, and Kleene developed definitions based on recursion schemes. Fortunately all of these definitions are equivalent, and each of many other definitions pro- posed later are also equivalent to Turing's definition. This has lead to the general belief that these definitions have got it right, and this assertion is roughly what we now call \Church's Thesis". A natural definition of computable function f on N allows for the possibility that f(x) may not be defined for all x 2 N, because algorithms do not always halt. Thus we will use the symbol 1 to mean “undefined". Definition: A partial function is a function n f :(N [ f1g) ! N [ f1g; n ≥ 0 such that f(c1; :::; cn) = 1 if some ci = 1. In the context of computability theory, whenever we refer to a function on N, we mean a partial function in the above sense. -
Introduction to the Theory of Computation Computability, Complexity, and the Lambda Calculus Some Notes for CIS262
Introduction to the Theory of Computation Computability, Complexity, And the Lambda Calculus Some Notes for CIS262 Jean Gallier and Jocelyn Quaintance Department of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104, USA e-mail: [email protected] c Jean Gallier Please, do not reproduce without permission of the author April 28, 2020 2 Contents Contents 3 1 RAM Programs, Turing Machines 7 1.1 Partial Functions and RAM Programs . 10 1.2 Definition of a Turing Machine . 15 1.3 Computations of Turing Machines . 17 1.4 Equivalence of RAM programs And Turing Machines . 20 1.5 Listable Languages and Computable Languages . 21 1.6 A Simple Function Not Known to be Computable . 22 1.7 The Primitive Recursive Functions . 25 1.8 Primitive Recursive Predicates . 33 1.9 The Partial Computable Functions . 35 2 Universal RAM Programs and the Halting Problem 41 2.1 Pairing Functions . 41 2.2 Equivalence of Alphabets . 48 2.3 Coding of RAM Programs; The Halting Problem . 50 2.4 Universal RAM Programs . 54 2.5 Indexing of RAM Programs . 59 2.6 Kleene's T -Predicate . 60 2.7 A Non-Computable Function; Busy Beavers . 62 3 Elementary Recursive Function Theory 67 3.1 Acceptable Indexings . 67 3.2 Undecidable Problems . 70 3.3 Reducibility and Rice's Theorem . 73 3.4 Listable (Recursively Enumerable) Sets . 76 3.5 Reducibility and Complete Sets . 82 4 The Lambda-Calculus 87 4.1 Syntax of the Lambda-Calculus . 89 4.2 β-Reduction and β-Conversion; the Church{Rosser Theorem . 94 4.3 Some Useful Combinators . -
Programming with Recursion
Purdue University Purdue e-Pubs Department of Computer Science Technical Reports Department of Computer Science 1980 Programming With Recursion Dirk Siefkes Report Number: 80-331 Siefkes, Dirk, "Programming With Recursion" (1980). Department of Computer Science Technical Reports. Paper 260. https://docs.lib.purdue.edu/cstech/260 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. '. \ PI~Q(:[V\!'<lMTNr. 11'1'1'11 nr:CUI~SrON l1irk Siefke$* Tcchnische UniveTsit~t Berlin Inst. Soft\~are Theor. Informatik 1 Berlin 10, West Germany February, 1980 Purdue University Tech. Report CSD-TR 331 Abstract: Data structures defined as term algebras and programs built from recursive definitions complement each other. Computing in such surroundings guides us into Nriting simple programs Nith a clear semantics and performing a rigorous cost analysis on appropriate data structures. In this paper, we present a programming language so perceived, investigate some basic principles of cost analysis through it, and reflect on the meaning of programs and computing. -;;----- - -~~ Visiting at. the Computer Science Department of Purdue University with the help of a grant of the Stiftung Volksl.... agem.... erk. I am grateful for the support of both, ViV-Stiftung and Purdue. '1 1 CONTENTS O. Introduction I. 'llle formnlislIl REe Syntax and semantics of REC-programs; the formalisms REC(B) and RECS; recursive functions. REC l~ith VLI-r-t'iblcs. -2. Extensions and variations Abstract languages and compilers. REC over words as data structure; the formalisms REC\\'(q). REe for functions with variable I/O-dimension; the forma l:i sms VREC (B) . -
Yale University B0082
U.S. Department of Education Washington, D.C. 20202-5335 APPLICATION FOR GRANTS UNDER THE National Resource Centers and Foreign Language and Area Studies Fellowships CFDA # 84.015A PR/Award # P015A180082 Gramts.gov Tracking#: GRANT12659441 OMB No. , Expiration Date: Closing Date: Jun 25, 2018 PR/Award # P015A180082 **Table of Contents** Form Page 1. Application for Federal Assistance SF-424 e3 2. Standard Budget Sheet (ED 524) e6 3. Assurances Non-Construction Programs (SF 424B) e8 4. Disclosure Of Lobbying Activities (SF-LLL) e10 5. ED GEPA427 Form e11 Attachment - 1 (1244-GEPA Statement2018) e12 6. Grants.gov Lobbying Form e13 7. Dept of Education Supplemental Information for SF-424 e14 8. ED Abstract Narrative Form e15 Attachment - 1 (1246-CES FLAS Abstract) e16 9. Project Narrative Form e18 Attachment - 1 (1245-CES FLAS Budget Narrative) e19 10. Other Narrative Form e67 Attachment - 1 (1234-InformationToMeetStatutoryRequirements (9)) e68 Attachment - 2 (1235-FLAS Applicant Profile) e71 Attachment - 3 (1236-Acronyms ESC) e72 Attachment - 4 (1237-Bojanowska CV 2018) e74 Attachment - 5 (1238-BIOS ForAPPwithTOC_YaleESC) e85 Attachment - 6 (1239-LetterOfReferenceMinjinHashbat) e244 Attachment - 7 (1240-LetterOfReferenceNellekeVanDeusen-Scholl) e246 Attachment - 8 (1241-LetterOfReferenceConstantineMuravnik) e248 Attachment - 9 (1242-CouncilMemberList) e250 Attachment - 10 (1243-CourseListForAPP_ALLYaleESC) e253 11. Budget Narrative Form e317 Attachment - 1 (1247-Section C Budget Narrative) e318 This application was generated using the PDF functionality. The PDF functionality automatically numbers the pages in this application. Some pages/sections of this application may contain 2 sets of page numbers, one set created by the applicant and the other set created by e-Application's PDF functionality. -
Thinking Literature Across Continents
THINKING LIT ER A TURE ACROSS CONTINENTS This page intentionally left blank ranjan ghosh • j. hillis miller THINKING LIT ER A TURE ACROSS CONTINENTS Duke University Press • Durham and London • 2016 © 2016 Duke University Press All rights reserved Printed in the United States of Amer i ca on acid- free paper ∞ Typeset in Chaparral Pro by Westchester Publishing Services Library of Congress Cataloging- in- Publication Data Names: Ghosh, Ranjan, author. | Miller, J. Hillis (Joseph Hillis), [date] author. Title: Thinking lit er a ture across continents / Ranjan Ghosh, J. Hillis Miller. Description: Durham : Duke University Press, 2016. | Includes bibliographical references and index. Identifiers: lccn 2016024761 (print) | lccn 2016025625 (ebook) isbn 9780822361541 (hardcover : alk. paper) isbn 9780822362449 (pbk. : alk. paper) isbn 9780822373698 (e- book) Subjects: lcsh: Liter a ture— Cross- cultural studies. | Liter a ture— Study and teaching—Cross- cultural studies. | Culture in liter a ture. | Liter a ture and transnationalism. | Liter a ture— Philosophy. Classification: lcc pn61 .g46 2016 (print) | lcc pn61 (ebook) | ddc 809— dc23 lc record available at https:// lccn . loc. gov / 2016024761 Cover art: Kate Castelli, The Known Universe (detail), 2013. Woodblock on nineteenth-century book cover. Courtesy of the artist. CONTENTS vii Preface j. hillis miller ix Acknowl edgments ranjan ghosh xi Acknowl edgments j. hillis miller 1 Introduction: Thinking across Continents ranjan ghosh 9 Introduction Continued: The Idiosyncrasy of the Literary Text j. hillis miller PART I: The Matter and Mattering of Lit er a ture 27 Chapter 1. Making Sahitya Matter ranjan ghosh 45 Chapter 2. Lit er a ture Matters Today j. hillis miller PART II: Poem and Poetry 71 Chapter 3. -
Computer Algorithms As Persuasive Agents: the Rhetoricity of Algorithmic Surveillance Within the Built Ecological Network
COMPUTER ALGORITHMS AS PERSUASIVE AGENTS: THE RHETORICITY OF ALGORITHMIC SURVEILLANCE WITHIN THE BUILT ECOLOGICAL NETWORK Estee N. Beck A Dissertation Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY May 2015 Committee: Kristine Blair, Advisor Patrick Pauken, Graduate Faculty Representative Sue Carter Wood Lee Nickoson © 2015 Estee N. Beck All Rights Reserved iii ABSTRACT Kristine Blair, Advisor Each time our students and colleagues participate online, they face invisible tracking technologies that harvest metadata for web customization, targeted advertising, and even state surveillance activities. This practice may be of concern for computers and writing and digital humanities specialists, who examine the ideological forces in computer-mediated writing spaces to address power inequality, as well as the role ideology plays in shaping human consciousness. However, the materiality of technology—the non-human objects that surrounds us—is of concern to those within rhetoric and composition as well. This project shifts attention to the materiality of non-human objects, specifically computer algorithms and computer code. I argue that these technologies are powerful non-human objects that have rhetorical agency and persuasive abilities, and as a result shape the everyday practices and behaviors of writers/composers on the web as well as other non-human objects. Through rhetorical inquiry, I examine literature from rhetoric and composition, surveillance studies, media and software studies, sociology, anthropology, and philosophy. I offer a “built ecological network” theory that is the manufactured and natural rhetorical rhizomatic network full of spatial, material, social, linguistic, and dynamic energy layers that enter into reflexive and reciprocal relations to support my claim that computer algorithms have agency and persuasive abilities. -
6.2 Presenting Formal and Informal Mathematics
PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. http://hdl.handle.net/2066/119001 Please be advised that this information was generated on 2021-09-27 and may be subject to change. Documentation and Formal Mathematics Web Technology meets Theorem Proving Proefschrift ter verkrijging van de graad van doctor aan de Radboud Universiteit Nijmegen, op gezag van de rector magnificus prof. mr. S.C.J.J. Kortmann, volgens besluit van het college van decanen in het openbaar te verdedigen op dinsdag 17 december 2013 om 12.30 uur precies door Carst Tankink geboren op 21 januari 1986 te Warnsveld Promotor: Prof. dr. J.H. Geuvers Copromotor: Dr. J.H. McKinna Manuscriptcommissie: Prof. dr. H.P. Barendregt Prof. dr. M. Kohlhase (Jacobs University, Bremen) Dr. M. Wenzel (Université Paris Sud) ISBN:978-94-6191-963-2 This research has been carried out under the auspices of the research school IPA (Institute for Programming research and Algorithmics). The author was supported by the Netherlands Organisation for Scientific Research (NWO) under the project “MathWiki: a Web-based Collaborative Authoring Environment for Formal Proofs”. cbaThis work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. The source code of this thesis is available at https://bitbucket.org/Carst/thesis. Contents Contents iii Preface vii 1 Introduction 1 1.1 Wikis and other Web Technology . .2 1.2 Tools of the Trade: Interactive Theorem Provers . .4 1.3 Collaboration or Communication . -
Michael Trott
Mathematical Search Some thoughts from a Wolfram|Alpha perspective Michael Trott Wolfram|Alpha Slide 1 of 16 A simple/typical websearch in 2020? Slide 2 of 16 Who performs mathematical searches? Not only mathematicians, more and more engineers, biologists, …. Slide 3 of 16 The path/cycle of mathematical search: An engineer, biologist, economist, physicist, … needs to know mathematical results about a certain problem Step 1: find relevant literature citations (Google Scholar, Microsoft Academic Search, MathSciNet, Zentralblatt) fl Step 2: obtain copy of the book or paper (printed or electronic) fl Step 3: read, understand, apply/implement the actual result (identify typos, misprints, read references fl Step 1) The ideal mathematical search shortens each of these 3 steps. Assuming doing the work; no use of newsgroups, http://stackexchange.com, …. Ideal case: Mathematical search gives immediate theSlide answer,4 of 16 not just a pointer to a paper that might contain the answer; either by computation of by lookup Current status of computability: • fully computable (commutative algebra, quantifier elimination, univariate integration, …) • partially computable (nonlinear differential equations, proofs of theorem from above, …) • barely or not computable (Lebesgue measures, C* algebras, …), but can be semantically annotated How are the 100 million pages of mathematics distributed? J. Borwein: Recalibrate Watson to solve math problems Cost : $500 million Timeframe : Five years Last years: Watson, Wolfram|Alpha Slide 5 of 16 Slide 6 of 16 Slide 7 of 16 Ask your smartphone (right now only SIRI) for the gravitational potential of a cube Slide 8 of 16 And in the not too distant future play with orbits around a cube on your cellphone: find closed orbits of a particle in the gravitational potential of a cube initial position x0 1.3 y 0 0 z0 0 initial velocity v x,0 0 v y ,0 -0.29 v z,0 0 charge plot range solution time 39.8 Slide 9 of 16 Returned results are complete semantic representations of the mathematical fact And, within Mathematica, they are also fully computable. -
School of Architecture 2016–2017 School of Architecture School Of
BULLETIN OF YALE UNIVERSITY BULLETIN OF YALE BULLETIN OF YALE UNIVERSITY Periodicals postage paid New Haven ct 06520-8227 New Haven, Connecticut School of Architecture 2016–2017 School of Architecture 2016 –2017 BULLETIN OF YALE UNIVERSITY Series 112 Number 4 June 30, 2016 BULLETIN OF YALE UNIVERSITY Series 112 Number 4 June 30, 2016 (USPS 078-500) The University is committed to basing judgments concerning the admission, education, is published seventeen times a year (one time in May and October; three times in June and employment of individuals upon their qualifications and abilities and a∞rmatively and September; four times in July; five times in August) by Yale University, 2 Whitney seeks to attract to its faculty, sta≠, and student body qualified persons of diverse back- Avenue, New Haven CT 0651o. Periodicals postage paid at New Haven, Connecticut. grounds. In accordance with this policy and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against Postmaster: Send address changes to Bulletin of Yale University, any individual on account of that individual’s sex, race, color, religion, age, disability, PO Box 208227, New Haven CT 06520-8227 status as a protected veteran, or national or ethnic origin; nor does Yale discriminate on the basis of sexual orientation or gender identity or expression. Managing Editor: Kimberly M. Go≠-Crews University policy is committed to a∞rmative action under law in employment of Editor: Lesley K. Baier women, minority group members, individuals with disabilities, and protected veterans. PO Box 208230, New Haven CT 06520-8230 Inquiries concerning these policies may be referred to Valarie Stanley, Director of the O∞ce for Equal Opportunity Programs, 221 Whitney Avenue, 3rd Floor, 203.432.0849.