Origins of the Cognitive Revolution

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Origins of the Cognitive Revolution

• October 7, 1998

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The Cognitive revolution in

• Linguistics
• Psychology
• Computer science
• Philosophy
• Anthropology, sociology...

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Cognitive metatheory (Baars)

• What are we talking about (when we talk about
  cognitive science)? Cognitive metatheory (Baars)
  "a belief that psychology studies behavior in
  order to infer unobservable explanatory
  constructs, such as "memory," "attention," and
  "meaning." (144). "The cognitive revolution took
  place in many places at the same time, and
  involved a number of areas, including memory,
  language, imagery, and attention. (147)a
  metatheory that encourages one to infer
  unobservable theoretical constructs from
  empirical observations. (158).

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Howard Gardner

• "a contemporary, empirically based effort to
  answer long-standing epistemological questions --
  particularly those concerned with the nature of
  knowledge, its components, its sources, its
  development, and its deployment."(6)

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• Gardner's list of key components of cognitive
  science
• 1. Mathematics and computation by the 1950s,
  scientists were comfortable with the idea of an
  algorithm that could be specified in very general
  terms, and which could in principle be computed
  automatically. Mathematical proofs were
  themselves now something that could be studied
  mathematically (David Hilbert, Kurt Gödel)
  mathematical truth could be viewed as formal
  consistency.

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David Hilbert 1862 -1943
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Kurt Gödel 1906 -1978
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John von Neumann Born in Hungary 1903 - 1957.
Early work on mathematical foundations of
quantum mechanics (operators in Hilbert space).
Working on Gödel's problem when he cracked
it. Credited with the design of the modern
computer. http//www-groups.dcs.st-andrews.ac.uk/
history/Mathematicians/Von_Neumann.html
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John von Neumann

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• Gardner's List 2. The neuronal model
• McCulloch and Pitts showed that "anything that
  can be exhaustively and unambiguosuly described
  ...is...realizable by a suitable finite neural
  network." (von Neumann).
• Claude Shannon's MA thesis similar property of
  relay circuits.
• Thus binary circuits can embody logical
  statements.

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• Gardner's themes
• 3 The Cybernetic Synthesis
• The core idea the nervous system operates in a
  continuous relationship of feedback with the
  environment, modifying its activity in order to
  best satisfy achievement of the current
  goal-state (a future, not-yet-achieved state).

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• Gardner's Themes 4. Information theory
• Claude Shannon (electrical engineer at MIT and
  Bell Labs)
• showed that there was a quantifiable notion of
  information. Information is what is not redundant
  in a message. What was critical was showing that
  these were hard, cold items submissible to
  mathematical analysis.

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• Shannon suggested that the information content of
  a communication channel was equal to
• S pi log (pi)

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• Norbert Wiener "Information is information, not
  matter or energy. No materialism which does not
  admit this can survive at the present day."
  (1961).

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• Gardner's themes
• 5. Neuropsychological syndromes the study of
  aphasias, and many other function disruptions
  caused by brain lesions.

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• Howard Gardner's "key features of cognitive
  science"
• Representations
• Computers
• De-emphasis of affect, context, culture, and
  history
• Belief in interdisciplinary studies
• Rootedness in classical philosophical problems

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Cognitive revolution

• dealing with problems of mind as problems of
  information-processing.
• an algorithm (an explicit set of formal steps)
  to modify digital information.

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The impact of technology on themetaphors that
guide our thinking about the mind Daugman 1990

• "...the water technology of antiquity
  underlies...the Greek pneumatic concept of the
  soul...
• "...the clockwork mechanism proliferating during
  the Enlightenment are ticking with seminal
  influence inside"

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• la Mettrie's L'Homme Machine (1748)
• "...Victorian pressurized steam engines and
  hydraulic machines are churning underneath
  Freud's hydraulic construction of the
  unconcsicous and its libidinal eocnomy
• "the arrival of the telegraph network provided
  Helmholtz his basic neural metaphor, as did
  reverberating relay circuits and solenoids for
  Hebb's theory of memory...

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• "...it would be folly for us to regard the recent
  computer bewitchment of theoretical work ... as
  an entirely different kind of breakthrough in the
  history of ideas....
• "Yet there are many ...who ask precisely that we
  not think of computation as just the contemporary
  metaphor, but instead that we adopt it as the
  literal description of brain function..."

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• "Thus, for example, Zenon Pylyshyn complains that
  'there has been a reluctance to take computation
  as a literal description of mental activity, as
  opposed to being a mere heuristic metaphor...'"

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• "It might be said that a cornerstone of Western
  thought ... is the notion that persons are
  embodied spirits....Michaelangelo's Sistine
  fresco of Adam...Descartes...Pygmalion...
  Pinocchio...Genesis...Frankenstein."
• Hydraulic and mechanical metaphors
• Began in pre-Socratic thought, with four humours
  (Hippocrates) phlegm, bile (black, yellow), and
  blood. Evolved into Galen's animal spirits.

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• Clockwork Descartes
• I wish that you would consider all of these as
  following altogether naturally in this Machine
  from the disposition of its organs alone, neither
  more nor less than do the movements of a clock or
  other automaton from that of its coutnerweight
  and wheels...
• And the best-known of all,

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• de la Mettrie (L'Homme Machine)
• the human brain and body "a machine that winds
  its own springs -- the living image of perpetual
  motioin ...man is an assemblage of springs that
  are activated reciprocally by one another."
  (1747)

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• The hydraulic image reemerges in Freudian terms
  the urges which can, or cannot, be blocked or
  rechanneled by the conscious Ego.

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• Electrical switching of circuits. Remember that a
  circuit is a linear structure that must complete
  a loop electricity doesn't do this in nature --
  it's an accomplishment of human engineering.
• Circuits for power and circuits for telegraphs
  and telephones.

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• "The computational brain...notion was originally
  expressed...by McCulloch and Pitts (1943)
  University of Chicago, as we'll see that
  nervous activity embeds a logical calculus...
• "further explored ... by John von Neumann
  (1948)...Alan Turing had proposed in 1950 the
  famous "Turing test cognition can be tracked by
  language facility."

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• Turing earlier had shown that any algorithm can
  be implemented on a universal Turing machine,
  suggesting that one can study properties of
  algorithms independent of where they are
  implemented.

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• Wilfrid Rall "Some historical notes" (from
  Schwartz collection)
• McCulloch and Pitts (1943) "A logical calculus
  of the ideas immanent in nervous activity,"
  written while both were at the U of C (both moved
  to MIT in the years after WWII) both were during
  the war in the mathematical biology community led
  by Nicholas Rashevsky at the U of C.

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• Pitts was a grad student in mathematical
  biophysics, also worked with Rudolph Carnap in
  philosophy. At MIT he worked with Wiener (he
  never finished his PhD).
• Work during the early 1940s including "parallel
  interconnected neurons, dynamics of simple
  circuits, the general neural net, fluctuations of
  threshold..." .."a statistical consequence of the
  logical calculus of nervous nets (Dec 1943)."

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• Pitts a graduate student? That's what Rall says.
  But Jerry Lettvin, his best friend at the time,
  says Pitts was a perpetual outsider befriended by
  brilliant faculty, like Carnap and McCulloch and
  that Pitts was 18 years old, and had been kicked
  out by his family. (see Talking Nets, Anderson
  and Rosenfeld, MIT Press, 1998, p 3ff).

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• After the war, many physicists switched to
  biophysics. "One interesting and important topic
  presented in a course in the late 1940s was the
  concept of nonequilibrium steady states...."

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• September 1948 Hixon Symposium at Cal Tech
• Major addresses by John von Neumann on the
  digital computer (which he had been designing)
• Warren McCulloch (of whom we have spoken)
• Karl Lashley "The problem of Serial Order in
  Behavior".

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• Karl Lashley "The problem of Serial Order in
  Behavior". "The problems raised by the
  organization of language seem to me to be
  characteristic of almost all other cerebral
  activity." To wit spotlight on the complex
  organization of behavior. This complex behavior
  requires advance planning, of a hierarchical
  sort it cannot be analyzed as a series of acts,
  each caused by the environment and the previous
  act....

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• Lashley "Attempts to express cerebral function
  in terms of the concepts of the reflex arc, or of
  associated chains of neurons, seem to me doomed
  to failure because they start with the assumption
  of a static nervous system. Every bit of evidence
  available indicated a dynamic, constantly active
  system, or, rather, a composite of many
  interacting systems."

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• Summer 1956 Dartmouth conference
• Early lights in computer science
• Marvin Minsky
• John McCarthy LISP, MIT then Stanford AI labs
• Allen Newell
• Herbert Simon-- Newell and Simon wrote Logic
  Theorist (1955).

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• Newell and Simon strong functionalists
• With Shaw, they wrote in 1964
• We do not believe that this functional
  equivalence between brains and computers implies
  any structural equivalence at a more minute
  anatomical level...Discovering what neural
  mechaisms realize these information processing
  functions in the human brain is a task for
  another level of theory construction. Our theory
  is a theory of the informaiton processes involved
  in problem-solving and not a theory of neural or
  elctronic mechaisms for information processing.

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• Influential writing of Konrad Lorenz and Niko
  Tinbergen coming out of Europe on ethology
  biological determinants of animal behavior.
• Discovery of critical periods in animal
  development. (This influence is palpable in
  Chomsky's review of Skinner's Verbal Behavior, in
  Language 1956)

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• Getting ahead of ourselves, to Newell and Simon's
  view
• all intelligent systems involve physical symbol
  systems a control, a memory, a set of
  operations, input and output. Involves production
  systems -- an operation which is carried out if a
  certain specific condition is met. "Programs
  consist of long sequences of such production
  systems operations on the data base." (Gardner).

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September 11 1956 MIT Symposium on Information
Theory Alan Newell and Herbert Simon "Logic
Theory Machine" (proof generator) Noam Chomsky
"Three Models of Language" George Miller Magic
number 7 plus or minus 1.
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Newell and Simon wrote, One can date the change
roughly from 1956 in psychology, by the
appearance of Bruner, Goodnow, and Austin's Study
of Thnking and Miller's "Magical number seven"
in linguistics, by Noam Chomsky's "Three models
of language" and in computer science, by our own
paper on the Logical Theory Machine.
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Also in this period von Neumann's (posthumous,
1958) The Computer and the Brain
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• Linguistics
• Major influence of Noam Chomsky starting in the
  1960s graduate program begins in 1962 at MIT in
  linguistics, with Chomsky and Morris Halle.

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• Rapid growth of transformational syntax and
  phonology
• 1965 Aspects of the Theory of Syntax
• 1968 Sound Pattern of English
• 1965 presented what Chomsky called the Standard
  Theory -- the Aspects model -- which many took to
  be a statement about semantics

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• Semantic interpretation
• Deep Structure Phrase structure rules
• Surface structure
• Phonology
• The Standard/Aspects model

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• Two conceptions of what doing grammar is (Huck
  and Goldsmith 1995)
• Mediationist view Grammar is the component that
  links the order of words to the logical form, and
  the study of grammar is the decoding of that
  translation system.
• Distributionist view The study of grammar
  reveals the principles governing where the
  morphemes of a language may appear.

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• This led to a major split in the area of syntax,
  pitting Chomsky and many students at MIT against
  George Lakoff, Haj Ross, Paul Postal, and Jim
  McCawley.
• When the dust had settled, all five were doing
  different things -- roughly speaking.

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• Chomsky did little new syntax between 1967 and
  1977, then developed the principles and
  parameters/ Government and Binding approach
  (first, the Pisa lectures).
• Jim McCawley continued his work on logic and
  syntax.
• Haj Ross worked on freezes and poetry in 1985
  left MIT.
• Paul Postal developed Relational Grammar,
  Arc-Pair Grammar
• George Lakoff developed Cognitive ...

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• George Lakoff developed Cognitive grammar
  heavily involved with studies of metaphor and
  constrution grammar. (See his description in
  interview in Huck and Goldsmith 1995.)

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• But in the messages that generative grammar sent
  to the world were
• 1. The real goal is not good grammars of
  languages, but explanatory adequacy, i.e.,
  explanations of particular languages based on
  principles that are intended to be truths about
  all languages (Language).
• 2. Formal expression was crucial to quote Bacon,
  truth comes more easily from error than confusion.

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• 3. Deep insights will come from analyses where
  surface, or apparent, complexity is decomposed
  into a series of ordered modifications
  (derivation), which are the effects of a series
  of ordered rules.
• 4. There is no discovery procedure, no algorithm
  that takes data in and sends out a grammar
  rather, there is an evaluation measure...

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• In Syntactic Structures, Chomsky sketched three
  positions
• 1. Data Grammar
• 2. Data
• Grammar Yes/No
• 3. Data
• Grammar 1 G1 gt G2
• Grammar 2

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• These 3 positions demand successively less of
  Universal Grammar, but Chomsky said only the 3rd
  was practically doable.
• Thus he said UG could assign a complexity measure
  (or an evaluation metric), and a grammar with
  less complexity is better than a grammar with
  higher complexity.

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• It was clear that no learning theory conceivable
  in the 1950s could learn a generative
  transformational grammar. But if our innate
  schema contains the important structure, then
  learning is less important.