Concepts and knowledge Flashcards
Concepts
- General knowledge of a category
- mental representation of a category held in semantic memory
Categories
Items that are grouped together according to concept, often concepts and categories are used interchangeably
Exemplars
Individual items within a category
Our multi-dimensional way of organizing concepts allow us to access them at different ____
Levels
3 levels of concept specificity
- Superordinate level
- Basic level
- Subordinate level
Superordinate level
General terms for concepts (e.g. fish)
Basic level
- Gives more specificity to the concept (e.g. shark is a fish)
- How we usually talk about things (we have a bias toward basic level in communication)
Subordinate level
- More detailed specific representation of a concept
e.g. this shark is a hammerhead
Order of levels in the development of concepts
Basic, superordinate, then subordinate concepts
Semantic dementia patients level of concepts
- Early in disease, basic level concepts are accessed
- A dog is a dog
- As the disease progresses, use general concepts
- A dog is an animal : accessing basic level is impaired, subordinate level instead
Cognitive economy
Use the simplest terms that is still meaningful for the situation
E.g.
General public : piano
Piano players : Casio privia
Graded concept organization
Grades how well a certain item can belong to a concept (e.g. trout is more representative of a fish than a shark)
Concept inclusivity
Ability to refer to a single object on more than one level
E.g. violin and instrument
Generalization
- Process of deriving a concept from specific experiences
- See examplars that seem to be linked together and figure out their communality to class new items as belonging to this concept category
Classic approach to concept learning
Concepts involve forming rules about lists of features
Defining features (classic approach to concept learning)
necessary and sufficient for category membership
e.g. a dog has to be a living thing
Characteristics features (classic approach to concept learning)
Common but not essential for category membership
Solution to the problem that not all examplars that we know are part of a concept have defining features (classic approach to concept learning)
- Feature comparison between encountered items and list
- Refines what a defining features is for a concept
The classic approach to concept learning does not work well for…
- Complex concepts that are subject to variability (e.g., a fur-less dog)
- Ambiguous concepts: ‘student’; a ‘bachelor’ … a ‘hot dog’
The Cube Rule
- Rules to define what food is based on starch position
According to this rule, a hot dog is a taco
Similarity-based approach
You use the similarity between items rather than any sort of explicit rule rule to figure out if something new you see, an exemplar instance, belongs to their concept.
According to the similarity-based approach, items are defined by their resemblance to …
A collection of features (more than just defining features like in the classic approach)
Fuzzy boundaries
Items are, more or less, part of a category
* An item can be categorized into more than one category
E.g. a sled can be a vehicle or toy depending on the context
Steps of concept learning
- We start off trying to learn simple rules and list of features to define a concept.
- We’ll test hypotheses to try to refine those rules.
- With more knowledge and exposure, then we might start to use more similarity based representations of concepts (network of similarity)