chapter 9 knowledge
Collins and Loftus model
-tried to abandon problems of the semantic network by using short or longer links depending on the relatedness and interconnections b.w formerly linked concepts -said the spacing b/w concepts can differ for varous ppl depending on their experience and knowledge about specfic concepts
Connectionist model
Approach to creating computer models for representing concepts and thier properties based on characteristics of the brain -concepts are represented by activity that is ditributed across a network
Hierarchiacal organization
Basic idea that larger categories can be split up into more specific or smaller categories Rosch: by this process 3 levels of categorization are created; Superordinate, Basic and Subordinate.
levels of categories
Basic-Guitar or animal Subordinate-Electric Guitar or dog Superordinate-Musical Instrument or Lab
Collins and Quillan:Semantic network
Collins and Quillan: concepts are arranged in networks that represent the way concepts are organized in the mind. Network: -consists of nodes connected by links -nodes represent a category or concept -concepts are placed in network so related concepts are connected -properties assoicated with each concept indicated at that nodes -links connecting nodes indicate they are related to each other in the mind, the relationship b.w the objects ex: an assoiation in mind b/w canary and bird and b/w bird and animal -links indicate the kind of relation of objects by thier length -is hierarchical model bc consists of levels arranged so more specifc concepts are at bottom, more genderal at higher levels IN OTHER WORDS: concepts of out mental dictionary are represented by nodes, which in this net work represent a piece of knowlege about the world PROBLEM: cannot explain typicality effect -model supported by results of experiments using sentence varification technigue
lexical decision task
Decide as fast as you can if a letter string is a word or nonword -proposed that this might have occured b/c retrieving one word from memory triggered a spreading of activation to other nearby locations in a network in the mind
Definitional approach to categorization
Determine category membership based on whether the object meets the definition of the category. Does not work well Not all members of everyday categories have the same defining features PROBLEMS: Definitions: Hard to define necessary and sufficient features Ambiguity: Sometimes unclear whether an item belongs in a certain category Typicality: Some examples are better members than others
expertise play is categorization
Experts play more attention to specific features of objects in there area then noneperts -knowledge and experience of ppl affect categorisation -for experts basic level becomes superordinate
high vs. low prototypicality
High prototypicality: a category members closely resemble the category prototype. Low prototypicality: a category members does not closely resemble the category prototype Rosch: describes variations within categories as representing differences prototypicality. ex: not all birds are like robbins/ blue jays a penguim is bird too. Experiment: presented with category title bird, task rate the extent to which each member represented category title, very good example, poor/not a memeber. Results:sparrow considered good member/ panguim considered poor example
Exemplar approach
Involves determing whether an object is similar to a standard object. An exemplar is an acual member of a category that a person has encountered in the past EXAMPLE: if person has encountered sparrows/robins in past each of these would be an examplar for category bird ADVANTAGES: doesnt discard info about a typical case within a category, bat in bird category. Can Also deal more easly with categories that have widel varying memebers, games -Can explain many of Rosch results which were used to support prototype approach. explains the typicality effect
concept
Mental representation that is used for a variety of cog functions. EXAMPLE: When thinking about cats you draw on your concepts of cats which includes info about what cats are, usually look like, behavior... IMPORTANT: for communitcation, conserves mental space, and predictors and generalization
Exemplar approach vs Prototype approach
People use both approaches to categorization. Prototype more important as people first learn about categories but later examplar information becomes important. Examplars: work better for small categories (us presidents) Prototypes: work better for larger categories (birds) -Changes with experience
Priming influence prototypicality
Priming: Presentation of one stimulus facilitates the response to another. Rosch:prototypical members of a category are affected by priming stimuli more then non-prototypical memebers Experiment: first, hears the prime that was the name of a color. 2 sec later saw a pair of colors side by side, indicated whether two colors were same/different. colors presented in 3 ways. 1.colors the same and good example of category 2.colors same but poor example of category (light blue/greens) 3. colors different colors from different categories (red/blue) RESULTS:important results from 2 color same groups b/c this condition priming resulted in faster judgement forprototypical good colors then nonprototypical poor colors. Meaning faster for primary greens being same then light green. REASON: when you hear word green you imagine a good (high prototypical) green
Typicality effect
The ability to judge highly prototypical objects more rapidly. OTHER WORDS:The more typical members of a category are classified faster than the less typical members of the category
Family resemblance
The core features that category members share; a given member of the category may have some but not necessarily all of these features, allows for some variation -proposed to deal with that problem that definitions often dont include all members of a category -things in a particular category resemble one another in a certain way. EXAMPLE: Chairs come is different sizes, shapes, and materials but every chair resembles other chairs in the same way
High prototypicality
True of high prototypicality objects: 1.high family resemblance 2.statments about them varified rapidly 3.are named first 4.affected more my priming
Prototype
Typical member of the category, the mental image or best example. Rosch: said the typical prototype based on an average of members of a category that are commonly experienced EXAMPLE:Prototype for the category "bird" based on some birds you usually see, robbin or blue jay, but dosent necessaly look exactly like a particular type of bird. -Prototype not acutal member of the category but is an average representation of the category
Aspects of connectionist model
concepts are represented in networks that consist of input units, hiden units, and output units. imformation about concepts is represented in these networks by a distribution activation of these units. units activated by stimuli from the environment input units send signals to hidden units which send signal to output units another feature: connection weights dtermines how signals sent from one unit either increase of decrease the activity of the next unit. this corresponds to what happens at a synapse high connection weights result in strong tendency to excite the next unit lower weights cause less excitation
Categorization
grouping things based on shared properties EXAMPLE: see vehicles on the street you place them into categories; car, SUV, Ford, us car... WHAT IT DOES: -helps us understand cases we have never see before -once you know something is in a category you know alot of general things about it -helps understand behaviors that we might otherwise find off
Categorization in infants
reseach says even infants are capable of primitive categorization (one category for mom and another for dad) and more sophisicated categorizations begins apprearing at 2 months The familiarty/novelty preference procedure has been used to determine the development of cateforization from global to basic to specific
prototypicality
term used to describe how well an object resembles the prototype of a particular category
Spreading activation
the process by which the activation of one concept also activates or primes other concepts that are linked to it EXAMPLE: moving through network from robbin to bird activates the node at bird but activation also spreads to other nodes in network. activating canary to bird pathway activates other concepts that are connected to bird, animal or other kinds of birds RESULTS:the additional concepts that receive this activation become primed and can be retrieved easily from memory
connectionist model learn
the process of learning always the system to make generalizations b/c similar concepts create similar pattern. EXAMPLE: afer knowing one car, the system can recognize similar patterns as other cars, or may even predict how other cars look like
