Chapter 9 - Knowledge Flashcards
(33 cards)
Conceptual Knowledge
knowledge that enables us to recognize objects and events and to make inferences about their properties
ex. When we encounter a new item or event in the world, how do we come to know what kind of thing it is?
➤ How do we tell which items in our environment are horses, bicycles, trees, lakes, newspapers?
➤ How do we tell dolphins from sharks, or planets from stars? What makes a lemon a lemon?
➤ What are the various kinds of ‘things’ in the world?”
Concepts
the mental representation of a class or individual; categories of objects, events, and abstract ideas
Category
possible examples of a particular concept
ex. “cats” includes tabbies, Siamese cats, Persian cats, wildcats, leopards
Categorization
the process by which things are placed in categories - seems like an automatic process. Becomes more difficult when you encounter something unfamilar.
Definitional Approach to Categorization
decide whether some- thing is a member of a category by determining whether a particular object meets the definition of the category
Definitions work well for some things, such as geometric objects. Thus, defining a square as “a plane figure having four equal sides, with all internal angles the same” works. However, for most natural objects (such as birds, trees, and plants) and many human-made objects (like chairs), definitions do not work well at all.
Family Resemblance
the idea that things in a particular category resemble one another in a number of ways.
instead of setting definite criteria that every member of a category must meet, the family resemblance approach allows for some variation within a category.
Prototype Approach to Categorization
membership in a category is determined by comparing the object to a prototype that represents the category
Prototype
a “typical” member of the category - not an actual member of the category but is an “average” representation of the category
proposed by Eleanor Rosch
Typicality
High typicality means that a category member closely resembles the category prototype and low typicality means that the category member does not closely resemble a typical member of the category.
Sentence Verification Technique
Edward Smith - a procedure to determine how rapidly people could answer questions about an object’s category
found that objects higher in typicality were responded to quicker - typicality effect.
Priming
presentation of one stimulus facilitates the response to another stimulus that usually follows closely in time
Exemplar Approach to Categorization
involves determining whether an object is similar to other objects. however, whereas the standard for the prototype approach is a single “average” member of the category, the standard for the exem- plar approach involves many examples, each one called an exemplar.
ADVANTAGE of the exemplar approach is that by using real examples, it can more easily take into account atypical cases such as flightless birds
Exemplars
actual members of the category that a person has encountered in the past
Hierarchical Organization
Rosch
Superordinate (Global) - Vehicle
Basic - Car
Subordinate (Specific) - Ford
When naming things, people tend to name at the BASIC level of categorization
Global if not really sure what it is and specific is they are very familar with the object or experts. Ex. Tanaka’s bird experiment - experts in birds labelled more specific than nonexperts.
Semantic Network Approach
concepts are arranged in networks - collin and quillians model
Collins and Quillian’s Hierarchical Model
consists of levels arranged so that more specific concepts, such as “canary” and “salmon,” are at the bottom, and more general concepts are at higher levels
criticism - couldn’t explain the typicality effect, in which reaction times for statements about an object are faster for more typical members of a category than for less typical members
Cognitive Economy
storing information just once at a higer-level node
Researchers also questioned the concept of cognitive economy because of evidence that people may, in fact, store specific properties of concepts (like “has wings” for “canary”) right at the node for that concept (rather than above)
Spreading Activiation
activity that spreads out along any link that is connected to an activated node.
ex. moving through the network from “robin” to “bird” activates the node at “bird” and the link we use to get from robin to bird
Lexical Decision Task
Meyer and Schvaneveldt
participants read stimuli, some of which are words and some of which are not words. Their task is to indicate as quickly as possible whether each entry is a word or a nonword. For example, the correct responses for bloog would be “no” and for bloat would be “yes.”
PRIMING
Connectionism Approach
or Parallel Distributed Processing (PDP)
approach to creating computer models for representing cognitive processes; connectionist models designed to represent concepts
propose that concepts are represented by activity that is distributed across a network
created connectionist networks
Connectionist Units
roughly equivalent to axons in the brain
Input units: units activated by stimuli from the environment - concept/representation
Hidden units: send signals to the output units.
Output units: properties
Connection Weight
determines how signals sent from one unit either increase or decrease the activity of the next unit. These weights correspond to what happens at a synapse that transmits signals from one neuron to another
Error Signal and Back Propagation Connectionist Network
Error Signal: erroneous responses in the property units
Back Propagation: signals are being sent backward in the network starting from the property units (output units).
Graceful Degradation
disruption of performance occurs only gradually as parts of the system are damaged (connectivist)
