Concepts / Categorization

Mental representations

LTM (Concepts are basic units)

Semantic Memory

Propositions: "Dogs" bark, Dogs have fur, Dogs are pets

Procedural Memory

Schemas

Rule based "What to do in a Restaurant"

Aquired by autobiographical experience

Forms of reps

by Rule / defintion

by Prototype

abstract, by relations

Compression and facilitation

Mental economy

Makes remembering more easiy: All cats have hearts

Predictions of behaviour

To guide action

A level of recognition

Naming

Semantic Classifacation

Familiarity: lov level

concept provides Meaning: Mental Lexicon

Categorizations not only natural but depend on purpose: "Things to take in case of fire"

Card Sorting

Attribute Lising

Neuropsychology

Connectionist models

Pros

Divides the world in distinct classes: taxonomies

Members

All or none are members

share a) neccessary and b) sufficient features

are equally good

Generality claims

All concepts are represented this way

Everybody represents in this way

Inheritance: Bird inherits all from animal but adds feathers

1. Some propertes in beginning / Most at end

Transitivity: A=B= C and C= A

Hierarchical. Food= Fruit or Vegatables

Bachelor: male, unmarried, adult

Collins & Quillian: Categorization takes longer for 2 levals

A canary is an animal > A canary is a bird

Cons

Everyday Concepts fuzzy not exact

Some Categories have no def. features

Example: Furniture / chair

No neccessary and sufficient properties for all chairs

Defined by functional /not defined by pyhsical properties

Typicality more important than defining features:

Wittgenstein: Games are similar

Some things dont have definitions - more holistic

Cats would still be cats even if turs out they are robots from mars

Does not explain Typicality effets

Varying Knowlege: Experts vs. Normal people

Bad RTs: RTs not a good predictor

is a dog an animal < Is a dog a mamal

Intransitivity: big ben = clock = furniture

Borderline Cases

McCloskey & Glucksberg: yes/no

bookends =furniture?: changes across people and time

Typical items: chair= furniture: high over time and people

Possilbly: Lack of knowledge

Where does red turn into orange

Types of Categories differ

Well defined (a triangle)

Fuzzy (red)

Categorization differ according to action / purpose

Barsalou: internal structure not fixed but viewpoint and task driven

Smith & Sloman: Two routes: Similarity or Route based depending on the task

Decision based

Prototype: Fast and Superficial: Fast decisions under uncertainty

Classical: Exact definitions needed: law

Explanation based

Theory: If thing need explanations: This guy is intoxicated: Thats why he jumps the pool

Essentialism: Consistent with (current) expertise

Categorizers differ

Experts: Definition driven

Novices: Similarity Driven

Prototype: Other members determined by comp with typical member

What is typicality: Having moreo cue valid features in common with prototype

In some natural objects, attributes cluster together

Weighting=Cue Validity= Some features more important than others e.g. bird=feathers

How we do it?

comparing of features with stored rep

More similar features - quciker match

Statistacl distribution determines weight

high typicality instances match on high weighted values

Calculate family resemblecne: one shared by 16, one by 14=30

Pros

Mervis & Roesch: < RT faster and less errors for typical examplars

Armstrong: defined cat seem to have typiclity: female: mother vs. policewoman

Dual Proces: conept core to judge generel membership, prototype to evlauate instances

Roesch and Mervis: Robins share more properties with other category member than penguins

Cons

Hampton: Some astract concepts (belief) has no prototype

Implies we only use lists of attributes but we also use reason: blue bird=probably "warrum," but fat man is prob not a "klatau"

Medin & Shoeben: typicality context dependent: kaffeelöffel paradox: large wooden>small wooden

Barsalou: goal derived categories have no family resemlance: presents that john likes

Semanitc Transfer?: Complex Concepts Lead to wrong interpretaions in real life: pet-fish = dog trout

Evaluation

Explains many categories that lack clear definitions (game, furniture)

Family resemblence often predicts typicality scores

Unclear Definition: Are prototypes lists or typical members?

Demarcatino Line (Classical View)

Typical members (Prototype views)

Problem with similarity: What properties are looked at? (Plumes and Lawnmowers-> knowledge makes the difference)

knowledge involved - not mere lists

Pros

Rips Pizza Dissotiation: More similar to quater but more likely (=categorized) a pizza

Kroska and Goldstone: 2 emo Szenario categorzed as fear but more similar to joy

Developemental Evi: Kiel: characterisic to defining shift

Looks and Behaves like Zebra: 4 yrs-zebra 7 yrs-horse

Racoon disguised as a skunk

Murpy: They dont know about biological categories

Evaluation

Good because it hints to problems with "similarity"

Underspciefied: How are complex categories/ theories combined?: pet fish

Its rather knowledge than theory

Bottom up: Facilitated by similarity

Top down: with more complex situations we have to think

Difference to classical view

We have a belief about essential prop

If we are not shure: we create a placeholder

Filling the placeholder is job of science

A placeholder can change

Pro

Gelmann and Wellman: a dog still dog if inside is taken (4-5 yrs: no)

Con:

Malt: People know, the essece of water is H20

Tears are not water although rated to contain 87% H20

Pond is water although judged to contain only 63% H20

Categorizatio also driven by function, location socio-historical context

Braisby: Is a cat still (essentially) a cat a cat even when robot from mars?

50 "Yes, cat

50% both true, fals

Concepts dirven by context and content

Malt: We are essentialist for natural categories

Trout-Bass: Ask an expert

Boat-Ship: Call it whatever

Braisby: Experts say it is a salmon: 25% modify their opinion to conform w. experts

Function and appearane are imp as well

IAC model: Can learn from specific instances and link comon characteristics: Links are knowledge / instances are strength of connections

Specific deficits for

Living things & Food

Fruit & Vegtables

body parts

With Alzheimers: Naming Superordinate: Horse--> Animal