1. Categories What are categories? The internal structure of categories Rule-based approaches Similarity-based approaches Theory-based approaches

2. What are categories Categorization is a huge topic How are people able to apply prior knowledge? –By recognizing a new situation as an instance of a previous situation. –Categorization is the process that allows this to occur Categories have many functions –Classification –Prediction –Reasoning –Communication

3. Start with classification The most highly studied function How to people learn to classify new items? Three approaches –Rule-based approaches –Similarity-based approaches –Theory-based approaches

4. Rule-based approaches Classical view of categories –A set of necessary and sufficient features Necessary feature to be in a category –All instances of that category must have it. Four sided Sufficient feature set –All instances of the category have the set of features –No instance not in the category has the set of features Four sided closed figure

5. Problems with rules It is hard to find a set of necessary and sufficient features for most categories Bachelor –Unmarried adult male –But what about a Catholic Priest or a widower? Maybe the definition is no good. –Almost any definition would have exceptions

6. Rule + Exception models Nosofsky and colleagues –Find a simple rule that classifies most items –Store the exceptions separately Model accounts for laboratory studies –Hard to see what else you could do with rules and exceptions –How would you make predictions, reason or communicate?

7. Similarity-based models A new exemplar is classified based on its similarity to a stored category representation Similarity –Degree of feature overlap between items. Types of stored category representations –Prototype –Exemplar

8. Prototype model Prototype: Average category member

9. Typicality gradient This model suggests that there are good and bad category members. –Can be seen with typicality ratings. Typicality decreases with distance from prototype.

10. Classification of Prototype If there is a prototype representation –Prototype should be easy to classify –Even if the prototype is never seen during learning –Posner & Keele

11. Exemplar model Exemplar: A category member Perhaps a category representation consists of storage of a number of category members New exemplars are compared to known exemplars

12. Exemplars and prototypes It is hard to distinguish between exemplar models and prototype models Both can predict many of the same patterns of data Graded typicality –How many exemplars is new item similar to? Prototype classification effects –Prototype is similar to most category members Current research focuses on other issues

13. Theory-based models Sometimes similarity does not help to classify. –Daredevil

14. Theories and development The use of theories increases with development Keil –Kids told about a cat given an operation Painted black with a white stripe A bag of smelly stuff put in its stomach It can shoot the smelly stuff –Young kids call this animal a skunk –Older kids call it a cat –Reflects a developing theory of biology

15. Psychological Essentialism People act as if categories are governed by rules We believe that there is something that makes an object what it is –Even if we do not know what that thing is. –We use this as a basis for predictions For living kinds: DNA? For nonliving natural kinds: Atomic structure? For artifacts: Function or intended function?

17. Summary Classical models Similarity-based models Theory-based models Human concepts use a combination of these