great detail is needed for planning & executing current responses

1. Review: more detail vs. less detail • great detail is needed for planning & executing current responses • some detail about context of new learning can be emcoded with that learning, and be a cue. • less detailed representation is more useful for learning general, widely-applicable lessons for future reference

2. Categorization My dog sleeping. My dog. All golden retrievers. All dogs. All canines. All mammals… Each of these is a category. Categorization is the process of deciding which details matter, and which don’t, for some purpose.

3. Advantage we gain by categorizing things: • Bruner, Goodnow, & Austin (1956): • reduce complexity of environment • generalize lessons • guide choice of response • make hierarchical knowledge available

4. Two questions about categories: • 1. What is the structure of natural categories like? • That is a question about the world. • How is information about natural categories represented in memory? • That is a question about your mind.

5. 1. The structure of natural categories • Is this a question about the world, or about us? • Which two are most similar: sheep, goats, cows? • To some extent, structure of natural categories is given by the world. To some extent, it is impressed upon the world by human cognition.

6. 1. The structure of natural categories • Most important work was done by Eleanor Rosch. • Hierarchy. • Rosch argued that our categorical knowledge is organized in a hierarchy: superordinate, basic level, subordinate. • This is a relation of containing.

7. Mammal Dogs Cats Horses Collie Airedale Persian Siamese Arabian There are three levels in this hierarchy. They are not all equal.

8. Basic level • The basic level is the most important one • Between superordinate and subordinate • It’s the one we use when we name an object. • It’s the one children learn first.

9. Shared characteristics Superordinate – items in a category can be very different from each other. E.g., table, chair, lamp. Subordinate – items in different categories can be very similar to each other. E.g., dining room chair, patio chair. Basic level – items similar to others in category, different from those in other categories.

10. Review - Hierarchy • Things in the world present themselves in a hierarchy of levels of categorization • At basic level, items in a category look like each other but not like members of other categories. • Basic level is one used spontaneously in naming objects.

11. Rosch’s second contribution - Typicality • Rosch argued that some members of a category are “better” than others – that is, more typical. • such members have ‘family resemblance.’ • typical members are similar to other members, unlike non-membersof category

12. 2. The representation of natural categories • Some categories are natural – e.g., mammals. • Some categories are artificial – e.g., all animals that weigh more than 100 lbs. • Some are functional: things to bring out of the house in the event of fire.

13. 2. The representation of natural categories Four models: Prototype Feature frequency Nearest Neighbour Average distance

14. Prototype models • A prototype is a typical member of a category • Prototype theories say that, through experience, we create a central example of each category. • Prototype may exist only in your mind (e.g., not as an actual object in the world).

15. Feature frequency • Categorization is based on how many features the to-be-classified object shares with each of the available categories. • E.g., a whale shares ‘breathes air’ and ‘gives birth to live young’ with mammals. It shares ‘lives in the ocean’ and ‘moves by tail and flipper action’ with fish. • So we should expect confusion about whales

16. Nearest Neighbour New object is compared with each exemplar of each stored category. Compute difference between object and each exemplar in each category. New object is classified in category containing object it is most similar to (smallest difference).

17. Average Distance Same comparison of new object to all stored exemplars of categories as in nearest neighbour. Decision based on which category has smallest average distance from the new object. Compare with Nearest Neighbour model – here, it is average distance for the category, not just which exemplar is closest, that counts.

18. Review – models of representation • Two fundamentally different views of how we store category information: • Prototype model • ‘what is generally true’ about something is stored and available when needed • this view emphasizes abstract representations

19. Review – models of representation • N.N. and A.D. models • ‘what is generally true’ is not stored, but computed when needed. • these views emphasize storage of individual experiences with objects