Origins of the Cognitive Revolution October 7, 1998 The Cognitive revolution in Linguistics Psychology Computer science Philosophy Anthropology, sociology... Cognitive metatheory (Baars) What are we talking about (when we talk about cognitive science)? Cognitive metatheory: (Baars) "вЂ¦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)вЂ¦a metatheory that encourages one to infer unobservable theoretical constructs from empirical observations. (158). 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) 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 GГ¶del); mathematical truth could be viewed as formal consistency. David Hilbert 1862 -1943 Kurt GГ¶del 1906 -1978 John von Neumann Born in Hungary; 1903 - 1957. Early work on mathematical foundations of quantum mechanics (operators in Hilbert space). Working on GГ¶del'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 John von Neumann 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. 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 goalstate (a future, not-yet-achieved state). 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. Shannon suggested that the information content of a communication channel was equal to S pi log (pi) Norbert Wiener: "Information is information, not matter or energy. No materialism which does not admit this can survive at the present day." (1961). Gardner's themes: 5. Neuropsychological syndromes: the study of aphasias, and many other function disruptions caused by brain lesions. Howard Gardner's "key features of cognitive science": пЃ® Representations пЃ® Computers пЃ® De-emphasis of affect, context, culture, and history пЃ® Belief in interdisciplinary studies пЃ® Rootedness in classical philosophical problems Cognitive revolution dealing with problems of mind as problems of information-processing. = an algorithm (an explicit set of formal steps) to modify digital information. The impact of technology on the metaphors 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" 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... "...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..." "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...'" "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. 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, 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) The hydraulic image reemerges in Freudian terms: the urges which can, or cannot, be blocked or rechanneled by the conscious Ego. 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. "The computational brain...notion was originally expressed...by McCullo[ch] 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]." 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. 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. 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)." 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). 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...." 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". 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.... 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." Summer 1956 Dartmouth conference Early lights in computer science: пЃ® Marvin Minsky пЃ® John McCarthy: LISP, MIT then Stanford AI labs пЃ® Allen Newell пЃ® Herbert Simon-- Newell and Simon wrote Logic Theorist (1955). 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. 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) 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). 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. 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. Also in this period: von Neumann's (posthumous, 1958) The Computer and the Brain Linguistics: Major influence of Noam Chomsky starting in the 1960s: graduate program begins in 1962 at MIT in linguistics, with Chomsky and Morris Halle. 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: Semantic interpretation Deep Structure Phrase structure rules Surface structure Phonology The Standard/Aspects model 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. 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. 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 ... George Lakoff developed Cognitive grammar; heavily involved with studies of metaphor and constrution grammar. (See his description in interview in Huck and Goldsmith 1995.) 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. 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... In Syntactic Structures, Chomsky sketched three positions: 1. Data Grammar 2. Data Grammar 3. Data Grammar 1 Grammar 2 Yes/No G1 > G2 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. 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.