Concept Learning What do concepts do as long as us Communication Conserve mental space

Concept Learning What do concepts do as long as us Communication Conserve mental space

Concept Learning What do concepts do as long as us Communication Conserve mental space

Lady La,, Morning Show Host has reference to this Academic Journal, PHwiki organized this Journal Concept Learning What do concepts do as long as us Communication Conserve mental space Prediction in addition to generalization Organize our world Theories of concept learning Stimulus-response association Classical view Prototype model Exemplar model Stimulus-response learning (Hull, 1920) Passive (unconscious) learning to associate physical stimulus with a category label response

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Classical view (Bruner, 1956) Concept learning involves active hypothesis as long as mation in addition to testing Learning a concept means finding the right rule as long as determining whether something belongs in the concept Concepts are represented by rules Rules as necessary in addition to sufficient features Necessary feature: If something is a member of Concept C, then it must have Feature F “Yellow” Is necessary as long as concept Canary, “smelly” as long as Skunk Sufficient feature: if something has Feature F, then it must belong to Concept C “Eyes that see” is sufficient as long as concept Animal Rule-based categories Rule-based categories Square in addition to striped Square or striped If striped then square If striped then square If square then striped

Problems with the classical view Can’t specify defining features Wittgenstein on “games” Unclear cases People disagree with each other about categories People also disagree with themselves! Typicality Members of a category differ in how “good” or natural a member they are Penguins in addition to robins are both birds, but robins are more typical Typicality ratings Prototype Theory (Rosch, 1971) A Concept is represented by a prototypical item = central tendency Prototypes include characteristic features that are usually present, not only necessary or sufficient features Unclear cases h in addition to led An object may be equally close to two categories’ prototypes Typicality h in addition to led The typicality of an item is based on its proximity to the prototype Family resemblance The members of a category are overall similar, but there may not be anything that they all have in common

Prototype Theory Prototype Prototypical beach Prototypical mountain

Prototypical Eiffel Tower Family Resemblance An objective measure of typicality

What does typicality predict Typicality ratings Order of listing members of a category “Bluejay” listed be as long as e “Emu” as long as Bird category Response time to verify “An X is a C” “Yes” to “Are eagles birds” is slower than “Yes” to “Are sparrows birds” Inferences Generalization from typical item to category is stronger than from atypical item to category “All chickens/sparrows on a certain isl in addition to have a certain bacteria in their gut. How likely is it that all birds do” Higher probability estimates with sparrows than chickens R in addition to om Dot Pattern Experiment (Posner & Keele, 1968) Four r in addition to om dot patterns serve as category prototypes Participants see 12 distortions of each prototype Learn to categorize patterns with feedback Test categorization accuracy as long as Old distortions of prototype New distortions of prototype New distortions, further removed from prototype The hitherto unseen prototypes themselves Results Prototypes are categorized as well as old distortions Both are categorized better than new distortions The new, far-removed distortions are least well categorized With 2 week delay, the prototype is categorized most accurately Posner & Keele claim: prototypes are explicitly extracted from examples, in addition to serve as representation as long as category. Category A Category B Prototypes Never shown during traininng Distortions of prototypes

Sources of fuzzy categories Context-dependent categories (Labov, 1973) What counts as a bowl/cup depends on situation Multiple models (Lakoff, 1986) Different models of a concept may provide different categorizations. Typicality increases as more models agree with a categorization Mother as female who gives birth, female provider of genes, female who raises you, female married to your father, etc. Lying: not true, trying to mislead, know true answer Climbing: upward component, clambering motion Caricatures Caricatures – exaggerate distinctive features of an object Caricatures are more readily recognized than actual pictures Categories are often times represented by caricatures, rather than prototypes, because caricatures better discriminate between categories Size Color A A A A A B B B B B

Attractive faces are only average Combining more faces together increases attractiveness Automatic Caricature Creation Prototypes

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Automatic Caricature Creation Veridical line drawing Caricatures are recognized faster than actual line drawing Caricatures are well perceived because they exaggerate distinctive elements

Prototype Prototype of attractive subset of faces Caricature of attractive subset of faces

Dog in addition to bird experts identifying dogs in addition to birds at different levels Experts make subordinate as quickly as basic categorizations

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