1. Chapter Three of Green: Intro to Cogsci Spring 2005

2. 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”

3. Flow charts How to do it Example: Recipe Is oven on to 350? NO Yes Turn on to 350 Open Package

4. Box/arrows How it is done, from input to output Proximal Stimuli Perception of distal stimuli

5. 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.

6. Architecture and modularity What is cognitive architecture and how does it differ from the brain’s architecture?

7. Features of a Module 1.Domain specificity 2.Information encapsulation 3.Mandatory 4.Speedy (because of first three) 5.Shallow output representations 6.Same ontogency across species 7.Characteristic and isolatable breakdowns 8.Associated with a fixed and sometimes localized neural architecture Note: 6-8 & innately prespecified

8. Modularity in practice SAQ 3.1 3.2 3.3 3.4

9. Arguments for Saying Lang. System is innately specified –Babies knowledge of how lips should move. –Acquisition of the core elements of lexical and syntactic structure –Poverty of stimuli –Double disassociation (a without b AND b without a) Aphasia Linguisitic savant

10. Other Issues re modularity of lang system Domain specificity –McGurk effect (p. 66) Encapsulation –Parsing –Word recognition

11. 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

12. 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.

13. 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

14. 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?

15. Piaget Epigenetic constructivism Self-organizing system structured and shaped by its environment 3 basic operations and interactions with the environment explain adult cognition

16. 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.

17. Connectionism: Advantages?? Neurally more realistic? Learns in a way that allows generalizing – e.g., pattern learning/voice recognition Graceful degredation: unlike Turing machines

18. 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.”

19. Delta Rule Two advantages over Hebb Rule. What are they? 1.How they operate 2.What they operate on Why the Perceptron?

20. All or nothing rule

23. What have you Learned?