Spring 2001

Foundations of Cognitive Science

Cognitive Science 050.326/626

Prof. Paul Smolensky

T.A. Marina Todorova

 

Prerequisites:  At least one course at the 300-level or higher in cognitive science, psychology, computer science, linguistics, or philosophy of mind. Additionally, for 626: graduate standing.

Course goal:  To introduce students to the broad spectrum within cognitive science of: empirical methods, theoretical methods and frameworks, general conceptual issues, and major authors.  The course is short on concrete content, long on understanding and integrating the basic perspectives on cognition provided by multiple disciplines. The key skill focussed upon is logical argumentation.

Course theme:  Research on ‘neural network’ or ‘connectionist’ computational models will provide one concrete context in which to consider a number of general course themes. Several cognitive domains are considered, but language is the one most frequently discussed.

Course requirements:  Reading (mostly major works from the research literature); daily written work on readings; class attendance, and participation in class discussion. Graduate students will in addition write three integrative essays. The reading and writing demands of the course are rather high (undergraduates receive ‘W’ credit for the course).

 

Course Requirements

        Attendance and participation in class discussion is extremely important, as this is an entirely discussion-based class. The reading and writing demands of the course are rather high (undergraduates receive ‘W’ credit for the course). Friday work will likely need to be begun before classtime Thursday.

        Students will hand in a write-up for every reading at the beginning of the class meeting during which that reading is to be discussed. Students will have 4 'waivers' of this requirement, to use any time during the semester. (The goal of this requirement is to ensure that students have given sufficient thought to the day's reading prior to class to be able to contribute to a high-level discussion. Another goal is to gain experience in logically analyzing research papers, and in evaluating reasoned arguments in cognitive science.)

        Write-ups fall into two categories:  "prose" and "diagrams". 

        The prose write-ups' format is not prescribed, but they should by and large provide answers to the following sorts of questions:

(1) With what problems is the author mainly concerned?

(2) What are the author's main claims about these problems?

(3) What arguments are given to support these claims?

(4) On what methodologies are these arguments based?

(5) How do these claims relate to the major course issues?

(6) How do these claims relate to the claims of the other authors we've read?

Prose writeups should NEVER reiterate the reading. The writeups address the CONTENT of the paper, not the paper itself. (Not "First the author talks about this and then she talks about that.") If directly addressed to the point, and concise, such writeups may require less than a single page (single spaced). Two pages may be more realistic much of the time.

        The format for the "diagrams" write-ups is much more prescribed. These are formal diagrams of the logic of the reading -- at least a substantial portion of it. These argument diagrams will be discussed in class; to get the general idea, check the 7 posters on the wall of the corridor containing the Cog Sci classroom, Krieger 234. (This is an experiment and you are the guinea pigs ... we need to work together to make this work, but it will be well worth it.)

        Graduate students (in 626) will be expected to complete at least one diagram per week, starting in the second or third week; the other write-up each week can be in prose form if preferred.

        Undergraduates (in 326) will not be expected to begin diagramming until the second month of the class; then they too will be expected to submit at least one diagram per week, the other write-up each week being in prose form if preferred.

        Daily write-ups will not, in general, be checked in detail, simply assigned a grade on a 3- or 5-point scale based primarily on the degree of thought and effort exhibited. Some number of diagram writeups will be checked in more detail; the specifics will be determined later.

        At three times during the semester, graduate students will submit short essays (length to be negotiated); these essays will attempt to integrate the material encountered to date. Undergraduates are also encouraged to submit such essays for extra credit.

        There will be no exams and no final paper.

Late work/incompletes. Work handed in late will be marked down (one point per day), work more than a few days late will not be accepted, and no incompletes will be given, except for medical emergencies.

 

Reading Schedule

Reading Schedule: Foundations of Cognitive Science
Date

Reading

Alternate

Author’s discipline

Feb.     1

Issues & stuff

 

 

             2

McClelland et al. 1986

Sejnowski & Rosenberg 1987*

Psychology

             8

Plato, Aristotle, Descartes

 

Philosophy

             9

Locke, Hume, Kant

 

Philosophy

           15

Hebb 1949*

Rosenblatt 1958*

Neuroscience

           16

Lashley 1950*

Ungerleider & Mishkin 1982*

Neuroscience

           22

Lettvin et al. 1959*

McCulloch & Pitts 1943*

Neuroscience

           23

Turing 1950*; Clarke 1968

 

Computer Science/SciFi

Mar.    1

Skinner 1953; Chomsky 1959

 

Psychology, Linguistics

             2

Chomsky 1957|65|67*|86|88

 

Linguistics/Philosophy

             8

Putnam 1967*

Chomsky 1969*

Philosophy

             9

Newell & Simon 1972

Newell & Simon 1963*

Computer Science/Psych

           15

J. R. Anderson et al. 1979*

Anderson 1989

Psychology

           16

Marr 1982

Haugeland 1981

Computer Vision [Phil]

           29

Searle 1980*

 

Philosophy

           30

Hofstadter 1985

Hofstadter 1979

 

Apr.    5

Rosch 1978

 

Psychology

             6

Lakoff 1987

Talmy 1988

Linguistics

           12

Rumelhart & McClelland 1986*

Plunkett & Marchman 1993

Psychology

           13

Pinker & Prince 1988H

Lachter & Bever 1988H

Psychology & Linguistics

           19

McCloskey 1992

 

Psychology

           20

J. A. Fodor & Pylyshyn 1988H

Fodor 1975*

Philosophy & Psychology

           26

Smolensky 1991*

Fodor & McLaughlin 1990*

[Philosophy]

           27

Spelke 1994*; Elman et al. 1997

 

Ling & Psych & Neurosci

May    4

¿Smolensky 1988?

¿Smolensky 1994?

 

 

This schedule as of Feb. 1: subject to change.

 

Key:

pre-20th century philosophy: not primary reading; excerpts from B. Russell, A History of Western Philosophy

* = in the Cummins & Dellarosa Cummins (eds) collection (Minds, Brains, and Computers)

H = in the Pinker & Mehler (eds) collection (Connections and Symbols)

unmarked: photocopies available in Eisenhower Library (and Cognitive Science Department Reading Room)

 

General Methodological Topics

Major distinctions and issues

Theory- vs. data-centering

Theories of behavior vs. theories of mental knowledge vs. theories of brain function

Levels of cognitive analysis

Explanation vs. description

Formal vs. non‑formal theories

Computational vs. non‑computational frameworks

Representational vs. non‑representational frameworks

Competence vs. performance

Mind as structure processor vs. mind as statistical processor

Nativism vs. empiricism

Conscious vs. unconscious processes

Knowledge/concepts as rules/definitions vs. as examples

Inference and decision making: logic‑based vs. non‑rational approaches

Serial vs. parallel processing

Independent mental faculties ('modules') vs. interactionism

Localized vs. distributed neural embodiment

Situated vs. non-situated cognition

Research methods

              

Empirical methods

Theoretical methods

Introspection

Philosophical analysis

Linguistic generalization

Linguistic analysis

Empirical neuroscience

Computational and mathematical modeling

Experimental psychology

Theoretical psychology

              

Covert aphorisms of cognitive science

Philosophy of science

Science = Data        or  Data » Theory

Data = Experiments

Better theory = More data coverage

Serious constraint on theory Þ Data         or  AI, Philosophy Þ BS

Theory = Description

Theory = Empirical generalizations

Unmeasurable Þ Unscientific

Precise theory Þ Computer implementation

Precise theory Þ Mathematical formalism

Implausible (introspective intuition) Þ   False

Explanation Þ External (e.g., functional) justification

Internal explanation Þ Circular reasoning

Functional fable Þ Explanation

Demystification Þ Trivialization/Denigration

Simplification Þ Irrelevance

Model Þ Theory 

Substantive

Mind = Brain

Cognition = Behavior

Thought Þ ¬Logic

Mind Þ ¬Formal system

Knowledge = Experience

Knowledge = Rules

Concept = Definition

Category = Categorization

¬[Computational Þ Intentional]

Level of representation = Level of cognitive computation

Connectionism Þ Associationism

Connectionism Þ Empiricism

Neurally informed Þ Neural model

Language = X (= Communication; Words; Speech recognition)

 

Reading List

Books at the bookstore

Chomsky, N.  1965.  Aspects of the Theory of Syntax. MIT Press. [1/4 chapters]

Cummins, R. & Dellarosa Cummins, D.  2000.  Minds, Brains, and Computers: The Foundations of Cognitive Science.  Blackwell.

Pinker, S. & Mehler, J. eds.  1988.  Connections and Symbols.  MIT Press/Bradford Books. [2/3 chapters]

Russell, B.  1945.  A History of Western Philosophy.  Simon & Schuster. [9/31 chapters] Russell readings:

Title

Chapter

Pages:Paragraphs

[Plato:] The Theory of Ideas

XV

119-132

Plato's Theory of Immortality

XVI

138:2-140:3

Knowledge and Perception in Plato

XVIII

149-158

Aristotle's Metaphysics

XIX

162­-167

Aristotle's Logic

XXII

195-202

Descartes

IX

561:1-568

Locke's Theory of Knowledge

XIII

609:3-613:1

Hume

XVII

659-674

Kant

XX

706:3-708:1; 712:3-718:1

Readings

Anderson, J.R.  1989.  A theory of the acquisition of human knowledge. Artificial Intelligence 40:313-351.

Anderson, John. R., Kline, Paul J., and Beasley, Charles. M, Jr. 1979. A general learning theory and its application to schema abstraction. Psychology of Learning and Motivation 12.

Bechtel, W.  1988.  Philosophy of Mind:  An Overview for Cognitive Science.  Erlbaum. Chapter 1: Some perspectives on philosophy of mind, pp. 1-17. [optional reading]

Chomsky, N.  1959.  A review of B.F. Skinner's Verbal Behavior.  Language 35:26-58  [Sections 1-4,11; reprinted in Block, N. ed., 1980, Readings in Philosophy of Psychology, Harvard University Press, 48-63.]

Chomsky, N. 1957. Syntactic Structures.

Chomsky, N.  1965.  Aspects of the Theory of Syntax. MIT Press. Preface, pp. v-vii, and Chapter 1: Methodological Preliminaries, pp. 1-­62. [read §§1-4, pp. 3-27; skim §§5-7, pp. 27-47; read §8, pp. 47-59; skip §9, pp. 60-62.]

Chomsky, N. 1967. Recent contributions to the theory of innate knowledge. Synthese, 17:2-11.

Chomsky, N. 1969. Linguistics and philosophy. In S. Hook (ed.) Language and Philosophy. NYU Press.

Chomsky, N.  1986.  Knowledge of Language.  Praeger.  Preface, Chapter 1, pp. xxv-13.

Chomsky, N.  1988.  Language and Problems of Knowledge:  The Managua Lectures.  MIT Press.

Clarke, Arthur C. 1968. 2001: A Space Odyssey.

Elman, Jeffrey L., Bates, Elizabeth A., Johnson, Mark H., Karmiloff-Smith, Annette, Parisi, Domenico, and Plunkett, Kim. 1997. Rethinking Innateness: A Connectionist Perspective on Development. MIT Press.

Fodor, J.A. & Pylyshyn, Z.W.  1988.  Connectionism and cognitive architecture.  Cognition 28:3-71. [Reprinted in S. Pinker & J. Mehler (eds.), Connections and Symbols.]  [Skim §4; leaves 52 pp.]

Fodor, J. A. 1975. The language of thought: First approximations. The language of thought. Harvard University Press.

Fodor, Jerry A. and McLaughlin, Brian P. 1990. Connectionism and the problem of systematicity: Why Smolensky’s solution doesn’t work. Cognition 35.

Haugeland, J. 1981. Semantic engines: An introduction to mind design. Mind design. MIT Press.

Hebb, D.O.  1949.  The Organization of Behavior.  Wiley.  Introduction, pp. xi-xix, Chapter 4: The first stage of perception: growth of the assembly, pp. 60-78.  [Reprinted, with new introduction, in J.A. Anderson & E. Rosenfeld eds., Neurocomputing:  Foundations of Research, MIT Press/Bradford Books; pp. 43-56.]

Hofstadter, D.  1985.  Metamagical Themas.  Basic Books. Chapter 26:  Waking up from the Boolean dream, or, subcognition as computation, pp. 630-665.

Hofstadter, Douglas R. 1979. Gödel, Escher, Back: An Eternal Golden Braid. Basic Books.

Lachter, J. , and Bever, T.G. 1988. The relation between linguistic structure and associative theories of language learning : A constructive critique of some connectionist learning models. Cognition 28:195-247. [Reprinted in S. Pinker & J. Mehler (eds.), Connections and Symbols.]

Lakoff, G.  1987.  Women, Fire, and Dangerous Things.  University of Chicago Press.   Excerpts: Preface, pp. xi-xvii; Chapter 1: The importance of categorization, pp. 5-15; Chapter 2: From Wittgenstein to Rosch, pp. 56-67.

Lashley, K.S.  1950.  In search of the engram.  Society of Experimental Biology Symposium, 4: Psychological Mechanisms in Animal Behavior.  Cambridge University Press.  Pp. 454-455, 468-473, 477-480.  [Reprinted, with new introduction, in J.A. Anderson & E. Rosenfeld eds., Neurocomputing:  Foundations of Research, MIT Press/Bradford Books; pp. 57-67.]

Lettvin, J. Y., Maturana, H. R., McCulloch, W. S., Pitts, W. H. 1959. What the frog’s eye tells the frog’s brain. Proceedings of the Institute of Radio Engineers 47.

Marr, D. 1982. Vision. W. H. Freeman and Company.

McCarthy, J. 1968.  Programs with common sense.  In M. Minsky ed., Semantic Information Processing, MIT Press, 403-418.  [Reprinted, with new introduction, in R. Brachman & H. Levesque eds., 1985, Readings in Knowledge Representation, Morgan Kaufmann, pp. 299-307.]

McClelland, J.L., Rumelhart, D.E., & Hinton, G.E.  1986.  The appeal of parallel distributed processing.  In D.E. Rumelhart, J.L. McClelland & The PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition; Vol. 1: Foundations, 3-44. [Reprinted in Collins & Smith eds., pp. 52-72.]

McCloskey, Michael. 1992.  Networks and theories: The place of connectionism in cognitive science.  Psychological Science, 2:387-395.

McCulloch, Warren S. and Pitts, Walter. 1953. A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics 5.

Newell, A. & Simon, H.A.  1963.  GPS, A program that simulates human thought.  In E. A. Feigenbaum & J. Feldman eds., Computers and Thought, 279-293.  [Reprinted in Collins & Smith eds., pp. 453-460.]

Newell, A. & Simon, H.A.  1972.  The theory of human problem solving.  Prentiss-Hall,  Chapter 14. [Reprinted in Collins & Smith eds., pp. 33-51.]

Pinker, S. & Prince, A.  1988.  On language and connectionism:  Analysis of a parallel distributed processing model of language acquisition. Cognition 28: 73-194.  [Reprinted in S. Pinker & J. Mehler (eds.), Connections and Symbols.]  [Skim §4, skip §7 and appendix; leaves 47 pp.]

Plunkett, K., Marchman, V. 1993. From rote learning to system building: Acquiring verb morphology in children and connectionist nets. Cognition 48, 21-69.

Putnam, H. 1967. The ‘innateness hypothesis’ and explanatory models in modern linguistics. Synthese 17:12-22

Rosch, E. 1978. Principles of categorization. In E. Rosch & B.B. Lloyd eds., Cognition and Categorization, Erlbaum, pp. 27-48. [Reprinted in Collins & Smith eds., pp. 312-322.]

Rosenblatt, F. 1958. The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65.

Rumelhart, D.E. & McClelland, J.L. 1986. On learning the past tenses of English verbs. In J.L. McClelland, D.E. Rumelhart, & The PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition; Vol. 2: Psychological and Biological Models, pp. 216-271 [Skim pp. 248-260].

Schank, R. & Abelson, H.  1977.  Scripts, Plans, Goals, and Understanding.  Erlbaum.  Chapters 1-3, 1-68.  [Reprinted in Collins & Smith eds., pp. 190-223.]

Searle, J.R.  1980.  Minds, brains, and programs.  In The Behavioral and Brain Sciences,  3:417-424. [Reprinted in Collins & Smith eds., pp. 20-31.]

Sejnowski, Terrence J. and Rosenberg, Charles R. 1987. Parallel networks that learn to pronounce English text. Complex Systems 1.

Skinner, B.F.  1953.  Science and Human Behavior.  Macmillan. Excerpts: pp. 27-35, 62-66, 87-90. [Reprinted in Block, N. ed., 1980, Readings in Philosophy of Psychology, Harvard University Press, pp. 37-47.]

Smolensky, P.  1988.  On the proper treatment of connectionism.  The Behavioral and Brain Sciences, 11:1-23.

Smolensky, P. 1991. Connectionism, constituency, and the language of thought. In B. Loewer & G. Rey (Eds.), Meaning in Mind: Fodor and his Critics. Oxford: Basil Blackwell. 201–227.

Smolensky, P. 1994. Computational theories of mind. In S. Guttenplan (Ed.),  A Companion to the Philosophy of Mind. Blackwell Publishers. 176-185.

Spelke, Elizabeth. 1994. Initial knowledge: Six suggestions. Cognition, 50.

Talmy, L. 1988.  Force dynamics in language and cognition.  Cognitive Science, 12:49!-100.

Turing, A.M.  1950.  Computing machinery and intelligence.  Mind, 59:433-460.  [Reprinted in Collins & Smith eds., pp. 6-19.]

Ungerleider, Leslie G. and Mishkin, Mortimer. 1982. Two cortical visual systems. In D. J. Inles (ed.), Analysis of Visual Behavior. MIT Press.