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

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Contents List of Figures and Tables | ix Preface | xiii Who Is This Book Written For? | xiv Acknowledgements | xv Chapter 1. The Cognitive Sciences: One or Many? | 1 1.0 Chapter Overview | 1 1.1 A Fragmented Psychology | 2 1.2 A Unified Cognitive Science | 3 1.3 Cognitive Science or the Cognitive Sciences? | 6 1.4 Cognitive Science: Pre-paradigmatic? | 13 1.5 A Plan of Action | 16 Chapter 2. Multiple Levels of Investigation | 19 2.0 Chapter Overview | 19 2.1 Machines and Minds | 20 2.2 From the Laws of Thought to Binary Logic | 23 2.3 From the Formal to the Physical | 29 2.4 Multiple Procedures and Architectures | 32 2.5 Relays and Multiple Realizations | 35 2.6 Multiple Levels of Investigation and Explanation | 38 2.7 Formal Accounts of Input-Output Mappings | 40 2.8 Behaviour by Design and by Artifact | 41 2.9 Algorithms from Artifacts | 43 2.10 Architectures against Homunculi | 46 2.11 Implementing Architectures | 48 2.12 Levelling the Field | 51 Chapter 3. Elements of Classical Cognitive Science | 55 3.0 Chapter Overview | 55 3.1 Mind, Disembodied | 56 3.2 Mechanizing the Infinite | 59 3.3 Phrase Markers and Fractals | 65 3.4 Behaviourism, Language, and Recursion | 68 v
3.5 Underdetermination and Innateness | 72 3.6 Physical Symbol Systems | 75 3.7 Componentiality, Computability, and Cognition | 78 3.8 The Intentional Stance | 82 3.9 Structure and Process | 85 3.10 A Classical Architecture for Cognition | 89 3.11 Weak Equivalence and the Turing Test | 93 3.12 Towards Strong Equivalence | 97 3.13 The Impenetrable Architecture | 106 3.14 Modularity of Mind | 113 3.15 Reverse Engineering | 119 3.16 What is Classical Cognitive Science? | 122 Chapter 4. Elements of Connectionist Cognitive Science | 125 4.0 Chapter Overview | 125 4.1 Nurture versus Nature | 126 4.2 Associations | 133 4.3 Nonlinear Transformations | 139 4.4 The Connectionist Sandwich | 142 4.5 Connectionist Computations: An Overview | 148 4.6 Beyond the Terminal Meta-postulate | 149 4.7 What Do Output Unit Activities Represent? | 152 4.8 Connectionist Algorithms: An Overview | 158 4.9 Empiricism and Internal Representations | 159 4.10 Chord Classification by a Multilayer Perceptron | 162 4.11 Trigger Features | 172 4.12 A Parallel Distributed Production System | 177 4.13 Of Coarse Codes | 184 4.14 Architectural Connectionism: An Overview | 188 4.15 New Powers of Old Networks | 189 4.16 Connectionist Reorientation | 193 4.17 Perceptrons and Jazz Progressions | 195 4.18 What Is Connectionist Cognitive Science? | 198 Chapter 5. Elements of Embodied Cognitive Science | 205 5.0 Chapter Overview | 205 5.1 Abandoning Methodological Solipsism | 206 5.2 Societal Computing | 210 5.3 Stigmergy and Superorganisms | 212 5.4 Embodiment, Situatedness, and Feedback | 216 vi
Page 2 and 3: MIND, BODY, WORLD
Page 4 and 5: MIND, FOUNDATIONS OF COGNITIVE SCIE
Page 8 and 9: 5.5 Umwelten, Affordances, and Enac
Page 10 and 11: List of Figures and Tables Figure 2
Page 12: Table 2-1. Examples of the truth va
Page 15 and 16: happened in psychology. “One acco
Page 18 and 19: 1 The Cognitive Sciences: One or Ma
Page 20 and 21: The fragmentation of psychology is
Page 22 and 23: qualitatively different kinds of qu
Page 24 and 25: should we examine “cognitive scie
Page 26 and 27: discrete symbols stored in a separa
Page 28 and 29: Some researchers have attempted to
Page 30 and 31: tool, or by its designer. The perso
Page 32 and 33: experiments fall into new relations
Page 34: With the foundations of the three d
Page 37 and 38: level, one asks what physical mecha
Page 39 and 40: thinking was logic, then thinking m
Page 41 and 42: equation of thought is of the secon
Page 43 and 44: ewritten as “A is B,” which in
Page 45 and 46: combinations of the binary inputs p
Page 47 and 48: Vannevar Bush. This machine was a p
Page 49 and 50: In Lovecraft’s (1933) story, the
Page 51 and 52: given in Table 2-2 (Hillis, 1998).
Page 53 and 54: switch was closed matched the durat
Page 55 and 56: 2.6 Multiple Levels of Investigatio
Page 57 and 58:
mentioned in the current section ar
Page 59 and 60:
How does a Turing machine generate
Page 61 and 62:
The problem with reverse engineerin
Page 63 and 64:
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
Page 71 and 72:
Other developments in cognitive sci
Page 73 and 74:
and strong equivalence are reviewed
Page 75 and 76:
After establishing his own existenc
Page 77 and 78:
For it is a very remarkable fact th
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used to solve a complex problem by
Page 81 and 82:
In the code given above, recursion
Page 83 and 84:
The complex, clausal structure of a
Page 85 and 86:
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
Page 372 and 373:
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
Page 398 and 399:
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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Page 444 and 445:
Baddeley, A. D. (1990). Human memor
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Bernstein, L. (1976). The unanswere
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Brooks, R. A., & Flynn, A. M. (1989
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Chase, V. M., Hertwig, R., & Gigere
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Comrie, L. J. (1933). The Hollerith
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Dawson, M. R. W., Kelly, D. M., Spe
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Downing, H. A., & Jeanne, R. L. (19
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Fletcher, G. J. O. (1995). The scie
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Gjerdingen, R. O. (1989). Using con
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Hauser, M. D., Chomsky, N., & Fitch
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Hopcroft, J. E., & Ullman, J. D. (1
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Josephson, M. (1961). Edison. New Y
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Kolers, P. (1972). Aspects of motio
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Leahey, T. H. (1987). A history of
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Luria, A., Tsvetkova, L., & Futer,
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McNaughton, B., Barnes, C. A., Gerr
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conduit metaphor, 299-303, 308 cons
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motion correspondence problem, 375-
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Turing equivalence, 95, 152 Turing
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