Chapter Three of Green: Intro to Cogsci Spring 2005.
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Transcript of Chapter Three of Green: Intro to Cogsci Spring 2005.
![Page 1: Chapter Three of Green: Intro to Cogsci Spring 2005.](https://reader030.fdocuments.in/reader030/viewer/2022032606/56649e935503460f94b98ea6/html5/thumbnails/1.jpg)
Chapter Three of Green:
Intro to Cogsci Spring 2005
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Review: Boxes and Flows
• Needed with Crane• Flow Charts: Used to express procedure and
algorithms; boxes represent operations or decisions and arrows represent flow of control. “How to do it”
• Box/arrow diagram: boxes represent cognitive processes and arrows represent flow of information. “How it happens”
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Flow charts
• How to do it
• Example: Recipe
Is oven on to350?
NO
Yes
Turn on to 350
Open Package
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Box/arrows
• How it is done, from input to output
Proximal Stimuli
Perception of distal stimuli
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Review: Attractions of Turing
• Non-mental explanation of mental: a Turing machine does not have to understand meanings in order to perform its basic operations.
• Retains compositionality, systematicity and so productivity• Compositionality of X: meaning of X determined by parts
and rules of compostion.– Examples: Grass is green. Blood is red.
• Compositionality seems to give us sytematicity: can understand same rules, same elements combined differently.– Example: Grass is red. Blood is green.
• Productivity: potential infinite number of X’s can be understood.
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Architecture and modularity
• What is cognitive architecture and how does it differ from the brain’s architecture?
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Features of a Module
1. Domain specificity2. Information encapsulation3. Mandatory4. Speedy (because of first three)5. Shallow output representations6. Same ontogency across species7. Characteristic and isolatable breakdowns8. Associated with a fixed and sometimes localized neural
architectureNote: 6-8 & innately prespecified
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Modularity in practice
• SAQ 3.1
• 3.2
• 3.3
• 3.4
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Other Issues re modularity of lang system
• Domain specificity– McGurk effect (p. 66)
• Encapsulation– Parsing– Word recognition
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Parsing
• “When you are happy, visiting relatives…” [people, activity]– When you are happy, visiting relatives will enjoy your
home.– When you are happy, visiting relatives can be a good idea.
• Two views compatible with Fodorean modularity:– All interpretations present and then selected– Done in fixed order with no contextual influence on order
• Why is contextual influence important?• According to Green, evidence favors encapsulation
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Word Recognition:
• A possible problem for Fodorean modularity:
• Example: The player went to the coach.• Responding quicker = primed• Priming: Process faster/easier because of
earlier process.• Fodor: this is dumb association, not
informationally informed.
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The Frame Problem
• What is it?
• Why is it concerned with “central systems”
• Humans just do update their beliefs reasonably successfully.
• See Crane on relevance and Dreyfus
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How modular should the mind be?
• Marr and the principle of modular design
• Fodorean arguments for modularity:– We need some systems to be fast, automatic,
etc
• Fodor’s teleological argument for non-modularity: is it evolutionarily sensible?
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Piaget
• Epigenetic constructivism
• Self-organizing system structured and shaped by its environment
• 3 basic operations and interactions with the environment explain adult cognition
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Karmiloff-Smith
• Innate dispositions to attend to particular stimuli and some innate skeletal knowledge structures.
• Thinks information encapsulation is acquired, not inborn
• Questions poverty of stimulus argument: environments are more structured than we thought.
• Infant mind is very plastic.
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Connectionism: Advantages??
• Neurally more realistic?
• Learns in a way that allows generalizing – e.g., pattern learning/voice recognition
• Graceful degredation: unlike Turing machines
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Pattern associators
• Learning rule
• Activation function
• Which is the Hebb rule?
• Instead of “a little learning is a dangerous thing,” we can have “a lot of learning is a dangerous thing.”
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Delta Rule
• Two advantages over Hebb Rule.
• What are they?1. How they operate
2. What they operate on
• Why the Perceptron?
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All or nothing rule
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What have you Learned?