Mind, Body, World- Foundations of Cognitive Science, 2013a

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Index A acoustic paradigm, 305 action potential, 7, 89, 140 activation function, 129, 140–41, 144–45, 150, 152, 154–56, 159–60, 165, 173, 189–90, 193–94, 348 affordance(s), 12, 205, 209, 219–21, 230, 245, 255– 56, 261, 306, 319, 322–23, 392 algorithm, 19, 39, 41, 43–52, 56, 63, 73, 77, 98, 100, 106, 120, 161, 179–80, 182–83 all-or-none law, 140–42, 152, 348 aperture problem, 365–66 arbitrary pattern classifier, 150 Aristotle, 24, 56, 134–35, 226 artifacts, 7, 12, 20, 42–44, 76, 89, 98, 104, 236, 320, 419 artificial intelligence, 3, 6, 10, 93, 96–97, 128, 187, 250, 261, 284, 311, 318, 335, 343, 364 artificial neural networks, 8–9, 125–26, 128–30, 132, 140–41, 148–52, 177–78, 184, 186–90, 201, 203, 207–8, 282, 286–87, 289–91 Ashby, W. Ross, 217–18, 236, 260–61, 401, 421 on Homeostat, 218, 236–37, 260, 421 associationism, 72, 130, 133–36, 139, 148, 150, 187 association, 130, 133, 135–36, 139, 148 automata, 20–21, 60, 65, 72–73, 89, 243–44, 337 B behavioural objects, 305, 308 behaviourism, 2, 68, 72, 107, 132, 148, 407–10 being-in-the-world, 220, 319, 403 binary logic, 23, 25–26, 28 biologically plausible, 8, 125, 128, 137, 184, 199, 202–3, 282, 286, 333–34, 342, 403, 416 blocking, 191 Boole, G., 21, 23–26 brain imaging, 117–18, 246 Braitenberg, Valentino, 43 Braitenberg vehicle, 216–17, 242 bricolage, 228–29, 236, 422 Brooks, Rodney, 12, 222, 237, 244, 253, 321, 323, 325, 331, 338 C Cage, John, 269–70, 294–95 Cartesian dualism, 59, 77, 122, 206–7, 255, 260–61, 354, 419 Cartesian philosophy, 20, 58–60, 89, 113, 122, 126, 133, 135, 199, 206, 243, 254, 270, 281–82 central control, 266, 271, 294, 325–26, 331–34, 337, 356 central controller, 8, 200, 329, 331 central executive, 121, 256, 333–34 change blindness, 221, 366 Chinese room argument, 49 Chomsky, Noam, 65, 74, 350–51, 363, 408 Chomsky hierarchy, 73 Clark, Andy, 13, 209, 226, 231, 344–45 classical conditioning, 190–93, 195 classical music, 195, 265–75, 277, 279–81, 283, 285, 287, 289, 291–95, 299, 301, 305, 307–9, 311–13, 315 classical sandwich, 11, 91–92, 147, 201, 207, 215–16, 222–25, 231, 235, 260–62, 285, 329–30, 343 coarse code, 162, 171, 184, 186, 340 coarse coding, 184–86, 340, 356 cognitive dialectic, 399–401, 403, 405, 407, 409, 411, 413, 415, 417, 419, 421, 423 cognitive penetrability, 110–13, 115, 119 cognitive scaffolding, 12, 205, 209, 226–27, 230, 245, 248, 262, 270, 383, 395–96, 411 cognitive vocabulary, 85, 268, 315, 323, 348, 351– 56, 359, 398, 411 computer, 4–8, 21–22, 29–30, 33, 36–38, 76–78, 89–90, 93–95, 106, 199–200, 227, 327–31, 334–36, 383, 410–13 analog computer, 30 computable functions, 81–82 computation, 12, 22, 77, 89, 122, 229, 260, 329– 30, 335, 359, 371, 375–81, 385, 414–17, 419–20 computer simulation, 4, 37, 55, 93–94, 97, 100, 106, 109, 119, 129, 193, 215–16, 354, 383 digital computer, 1, 4, 6, 8, 21, 26, 29, 76–77, 89–90, 122–23, 199–200, 202, 334–35, 403, 410 conceptualization, 209–10, 226, 261–62, 303 485
conduit metaphor, 299–303, 308 constitution, 209–10, 262 constraint propagation, 371, 375 context-free grammar, 66–67, 69, 71 contingency, 149, 153–58 contingency theory, 149, 154–55, 157–58 credit assignment problem, 159–61 cybernetics, 4, 12, 40–41, 129, 205–6, 217, 236, 259, 261, 299, 405–7, 410 D decision tree, 179–83 definite features, 175–77 delta rule, 131, 139, 155–56, 158, 160–61, 165, 291 generalized delta rule, 131, 158, 160–61, 165, 291 Dennett, Daniel, 5, 47 depictive theory, 108–10, 112, 394 Descartes, R., 55, 57–61, 69, 78, 95, 113, 126, 133, 199, 206, 219–20, 235, 254, 259, 282 designation, 81, 83, 322–23, 352 dialectic, 357, 399–401, 403, 405, 407, 409, 411, 413, 415, 417–19, 421, 423 digital musical instruments, 304–6 direct perception, 12, 322–23, 353, 360 distributed memory, 136, 138, 333, 337 distributed representations, 162, 178, 285, 339, 343, 346–47, 356 dodecaphony, 293 double dissociation, 117, 223–24, 341–42 dynamical systems theory, 259–60, 350, 403 extended mind, 12–13, 209, 230–32, 235, 256, 262, 321, 325 extended mind hypothesis, 12, 231–32, 235, 262 F feature cues, 104–5, 193–94, 239, 241, 243 feature integration theory, 102–3, 380–82, 385, 388 feedback, 4, 12, 74, 131, 161, 205, 211, 216–18, 236, 244–45, 259–61, 291, 393, 405–7, 409 finite state automaton, 70–71, 73, 338 FINST, 385–87, 389–93 Flores, Fernando, 317–20, 323–24, 344 Fodor, Jerry, 47, 71–72, 114–16, 118, 150 folk psychology, 84, 398 formalist's motto, 81–83, 269, 354–55 forward engineering, 188, 206, 210, 218, 235–37, 248, 258, 262–63, 400, 420–22, 424 frame <strong>of</strong> reference problem, 235, 420 frame problem, 392 functional analysis, 56, 119–22, 235, 262, 420 functional architecture, 48–49, 256–57 function approximation, 149, 151, 348 G generalized delta rule, 131, 158, 160–61, 165, 291 geometric cues, 104–5, 118, 193–94, 243 Gibson, James J., 12, 220–21, 258, 353, 392, 407, 415 Gold's paradox, 72, 74 E EDVAC, 76, 329, 331, 336–37 ELIZA, 95–97 embodiment, 12, 130, 205–6, 208, 210, 216–17, 221–22, 230, 248, 256, 258, 266, 270–71, 282, 383 emergence, 135, 139, 254, 292, 301 empiricism, 126–27, 130, 133, 148, 158–59, 162, 190, 202, 235, 403 enactive perception, 205, 209, 219, 221, 230, 392, 394 equilibrium, 155–58 error evidence, 44–45, 56, 98, 104, 106, 188, 257 evolutionary psychology, 116 H Heidegger, Martin, 220, 317, 319 hidden unit space, 147, 158, 165–66, 171–72, 182 hierarchical, 46, 64–65, 115, 213, 222, 267, 274–78, 289 hierarchical organization, 46, 267, 274, 276, 278 Hobbes, Thomas, 20, 59, 134 Hopfield network, 287, 341 Hume, David, 135 486 Index
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MIND, BODY, WORLD
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MIND, FOUNDATIONS OF COGNITIVE SCIE
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Contents List of Figures and Tables
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5.5 Umwelten, Affordances, and Enac
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List of Figures and Tables Figure 2
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Table 2-1. Examples of the truth va
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happened in psychology. “One acco
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1 The Cognitive Sciences: One or Ma
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The fragmentation of psychology is
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qualitatively different kinds of qu
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should we examine “cognitive scie
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discrete symbols stored in a separa
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Some researchers have attempted to
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tool, or by its designer. The perso
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experiments fall into new relations
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With the foundations of the three d
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level, one asks what physical mecha
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thinking was logic, then thinking m
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equation of thought is of the secon
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ewritten as “A is B,” which in
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combinations of the binary inputs p
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Vannevar Bush. This machine was a p
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In Lovecraft’s (1933) story, the
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given in Table 2-2 (Hillis, 1998).
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switch was closed matched the durat
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2.6 Multiple Levels of Investigatio
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mentioned in the current section ar
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How does a Turing machine generate
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The problem with reverse engineerin
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2.10 Architectures against Homuncul
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out at any given time (Newell, 1980
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experiment, people write questions
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hypothesis (Dawson, 1998), is used
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Other developments in cognitive sci
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and strong equivalence are reviewed
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After establishing his own existenc
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For it is a very remarkable fact th
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used to solve a complex problem by
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In the code given above, recursion
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The complex, clausal structure of a
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within a phrase marker. The recursi
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new physical state, the direction i
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Bever, Fodor, and Garrett (1968) us
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found that informant learning permi
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derived, in the same way as new kno
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physical symbol system hypothesis:
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semantic lives, in which they have
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A device that can compute every pos
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contents of mental states and behav
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as being tokens of a particular typ
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-1.5 Grande Prairie Slave Lake Fort
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A production system is a general-pu
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in thinking about cognition without
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ased on informed judgment, and how
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paranoids. Forty practising psychia
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if they are weakly equivalent), acc
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Newell and Simon (1972) created a c
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is a property that is not local, bu
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A third approach to validating a mo
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growing variety of models of reorie
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are instructed to scan across the i
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paper (Pylyshyn, 1973), which propo
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location to the first. In this cond
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The packing problem is concerned wi
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I should like to propose a generali
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attempt to localize function. For i
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solution to the problem? For instan
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links between the two at the differ
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4 Elements of Connectionist Cogniti
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twentieth centuries (Warren, 1921).
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connectionist cognitive science dev
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via unsupervised learning (Carpente
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symbols. However, as connectionism
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Empiricist philosopher John Locke c
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The ability of A’s later activity
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In spite of the popularity and succ
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then become a different kind of net
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space, an entire row of a truth tab
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the only time that output unit acti
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The multilayer network illustrated
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input pattern in an all-or-none fas
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function such as the logistic. “N
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esponse is interpreted as represent
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define more complex probabilistic c
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A second condition of the perceptro
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esponses to determine the trigger f
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hidden unit computes its error by s
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The musical notation for the C majo
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and then determine the relationship
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In the pitch class representation u
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input signals coming from all of th
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chords. For instance, none of the h
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ecording or wiretapping (Calvin & O
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anding when a hidden unit’s activ
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classical form. This result suggest
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technique, the ID3 algorithm (Quinl
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Decision Point From Table 4-4 Equiv
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For example, mushrooms that were as
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color; that red, for instance, even
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When New Connectionism arose in the
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idea is to give the network as many
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in contiguity with the UR, the CS b
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stronger, or more intense, or faste
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simulations also revealed new pheno
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the correlation between the connect
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Given the breadth of connectionist
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were provided earlier in this chapt
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On the other hand, the functional n
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5 Elements of Embodied Cognitive Sc
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can do away with the body” (Hayle
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of the environment in which he find
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salesman’s tour increases linearl
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of the superorganism’s components
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next. Theraulaz and Bonabeau (1999)
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physical robot that acts like a Bra
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seriously as a contributor to the c
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to perception. Gibson (1966, p. 49)
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modules provide basic, general-purp
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several hours to complete a task (M
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Scribner’s own work (Scribner & T
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a virtual interface that was increa
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The embodied approach’s emphasis
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eorganizing the entire system. The
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understanding. The extended mind hy
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old clocks and gas meters” (Grey
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the British Association (Hayward, 2
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without feature cues. Their goal wa
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obot has stopped moving, and two ar
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cognitive science ventures to study
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the human brain (Gallese et al., 19
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y changing its facial expression, d
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others’ actions mind reading or m
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that others “are like me in being
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is illusory (Clark, 2003; Dennett,
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Even though an agent’s body can b
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interaction with the world are not
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The lofty goals of artificial intel
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This system is then placed in an in
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Reviewing the three approaches with
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For instance, the exposition uses i
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this interface, internal thinking,
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The conductor is not the only contr
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grouped into distinct auditory stre
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and stored in memory in a form diff
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theorize about mental processing be
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Krumhansl’s (1990) internalizatio
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mighty Alps, whose white and shinin
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The isolated genius is a recurring
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6.4 The Connectionist Approach to M
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will not occur (Gasser, Eck, & Port
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preferences (Bugatti, Flammini, & M
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The key feature from above is tonal
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The vein for which three hundred ye
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complexities of sound were produced
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Reich’s idea of a musical process
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orchestra brings the score to life
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meaning and that this meaning is so
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evaluation, interpretation, and des
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software objects can now evolve and
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instruments can serve as behavioura
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the case that Austro-German music i
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Interactions between perception of
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7 Marks of the Classical? 7.0 Chapt
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in this section. One context for th
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Critical to Vera and Simon’s (199
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Vera and Simon (1993) pointed out t
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physical scene that is being viewed
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the three schools of thought in cog
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was employed to work on the 1880 Un
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predefined value was reached (Willi
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Indeed, the interactions between a
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determine which production will act
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classical models they inspire are d
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a word in memory to be accessed in
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7.5 Local versus Distributed Repres
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Finally, different degrees of super
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to produce networks that are capabl
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e essentially embodied and embedded
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to question explicit rules as a mar
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the electronic circuits which perfo
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which make use of the knowledge att
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instance, meaningful, complex token
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constraints on symbol manipulations
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linguistic structures. That is, suc
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8 Seeing and Visualizing 8.0 Chapte
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an enormously high-quality visual w
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for the discovery of subjective sen
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The primary visual data caused by t
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A related phenomenon is inattention
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Spontaneously and by our own power,
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depends upon noticing and reacting
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this location. The affected locatio
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For our purposes, though, the above
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The nearest neighbour principle is
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8.5 Vision, Cognition, and Visual C
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Feature integration theory arose to
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(Pylyshyn, 2007, p. 32). Part of Py
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independent of those for processing
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(Pylyshyn & Storm, 1988). However,
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& Stanton, 1978; Sakata et al., 198
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that compose early vision, and whic
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with embodied cognitive science. Py
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esults by demonstrating that they a
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According to the index projection h
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9 Towards a Cognitive Dialectic 9.0
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summarizes that text visually by us
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Another way to illustrate the diffe
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tension? One approach to achieving
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interested in reformulating cogniti
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On the other side of the antagonism
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For instance, Simon’s (1969) earl
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was a low-level interpretation that
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computation approach appeals to ele
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etween scientific paradigms (Kuhn,
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each of the three schools of though
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It is pleasurable and easy to creat
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exploring how this problem might be
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References Abu-Mostafa, Y. S. (1990
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