Categories

• What are categories?

• The internal structure of categories

• Rule-based approaches

• Similarity-based approaches

• Theory-based approaches

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

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

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

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

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?

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

Prototype model• Prototype: Average category member

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Typicality gradient

• This model suggests that there are good and bad category members.– Can be seen with typicality ratings.

Bird Prototype

Robin Eagle Emu

Bird Prototype

Robin Eagle Emu

• Typicality decreases with distance from prototype.

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

Prototype Small Distortion

MediumDistortion

LargeDistortion

Prototype Small Distortion

MediumDistortion

LargeDistortion

Exemplar model• Exemplar: A category member

• Perhaps a category representation consists of storage of a number of category members

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• New exemplars are compared to known exemplars

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

Theory-based models• Sometimes similarity does not help to classify.

– Daredevil

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

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?

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Summary

• Classical models

• Similarity-based models

• Theory-based models

• Human concepts use a combination of these