cognitive psychology report

REPRESENTATION and ORGANIZATION of KNOWLEDGE

in MEMORY:Concepts, Categories,

Networks and Schemas

REPRESENTATION and ORGANIZATION of KNOWLEDGE in MEMORY:

Concepts, Categories, Networks and Schemas

1. How are representations of words and symbols organized in the mind?

2. How do we represent other forms of knowledge in the mind?

3. How does declarative knowledge interact with procedural knowledge?

INTRODUCTION

ORGANIZATION OF

DECLARATIVE KNOWLEDGE

ORGANIZATION OF DECLARATIVE KNOWLEDGE

-CONCEPT – the fundamental unit of symbolic knowledge (knowledge of correspondence between symbols and their meaning for example, that symbol “3” means three), an idea about something that provides a means of understanding the world.

-CATEGORY-is a group of items into

which different objects or concepts can be placed

that belong together because they share

some common features, or because they are

similar to a certain prototype.

ORGANIZATION OF DECLARATIVE KNOWLEDGEConcepts and Categories

Concepts and categories can be divided in various ways:

NATURAL CATEGORIES

ARTIFACT CATEGORIES

are groupings that occur naturally in the world like birds or tree.

are groupings that are designed or invented by humans to serve particular purposes or functions.

Natural and Artifact Categories are relatively stable and people tend to agree on criteria for membership.

On the contrary..

-CONCEPTS-are not always stable but can change. They are described not in words but rather in phrases.

they also appear to have a basic level (sometimes

termed as a natural level) of specificity, a

level within a hierarchy that is preferred to other

levels.

In general, the basic level is neither the most

abstract nor the most specific. This basic level can be manipulated by context or expertise.

The basic level is the one that most people find to be maximally distinctive. By means of training, the

basic level can be shifted to a more subordinate level.

For example, the more a person learns about cars, the more he or she is likely to make elaborate

distinction among cars.

Research suggests that the difference between experts and novices are not due to qualitative

mechanisms but rather quantitative differences in processing efficacy.

So, how do we decide what objects to put into

a category?

-FEATURE-BASED CATEGORIES

-PROTOTYPE THEORY

-THEORY BASED VIEW OF CATEGORIZATION

-SEMANTIC-NETWORK MODELS

-SCHEMATIC REPRESENTATIONS

FEATURE-BASED CATEGORIES: A DEFINING VIEW

the classic view of categories disassembles a concept into a set of featural components. All those features are then necessary (and sufficient) to define the category. This means that each feature is an essential element of the category. Together, the features uniquely define the category; they are defining features.

For a thing to be an X, it must have that feature. Otherwise it is not an “X”.

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The Problem:

1. Some categories do not readily lend themselves to featural analysis.

2. A violation of those defining features does not seem to change the category we use to define them.

In sum, the feature-based theory has some attractive

features, but it does not give a complete account of

categories.

PROTOTYPE THEORY: A CHARACTERISTIC VIEW

grouping things together not by their defining features rather by their similarity to an averaged model of the category.

PROTOTYPEis an abstract average of all the objects the category we have encountered before

CHARACTERISTIC FEATURE

describe (characterize or typify) prototype but are not

necessary for it.

So what exactly is a characteristic feature?

whereas a defining feature is shared by every single object in a category, a characteristic feature need not to be Instead, many or most instances possess each character feature..

Psychologists differentiate two kinds of categories: Classical concepts and Fuzzy Concepts.

CLASSICAL CONCEPTS FUZZY CONCEPTS

-Can be readily defined through defining features

-May be built on defining features

-Cannot be so easily defined

-Built around prototypes

Real-World Examples: Using ExemplarsSome Psychologists suggests that

instead of using a single abstract prototype for categorizing a concept, we use multiple, specific exemplars.

EXEMPLARS are typical representatives of a category

In particular, categories are set up by creating a rule and then by storing examples as exemplars. Objects are then compared to the exemplars to decide whether or not they belong in the category the exemplars represent.

A SYNTHESIS: COMBINING FEATURE-BASED and PROTOTYPE THEORIIES

A full theory of categorization can combine both defining and characteristic features, so that each category has both prototype and a CORE.

CORE refers to the defining features something must have to be considered an example of category.

The prototype encompasses the characteristic features that tend to be typical of an example but that are not necessary for being considered as an example.

The core requires that someone labeled as a robber be a person who takes things from others without permission. The prototype, however, tends to identify particular people as more likely to be robbers.

“ROBBER”

A departure from feature-based, prototype-based, and exemplar-

based views of meaning is a THEORY BASED VIEW of meaning

also sometimes called an EXPLANATION-BASED VIEW.

HOW DO PEOPLE USE THEIR THEORIES FOR CATEGORIZATION?

A THEORY BASED VIEW OF MEANING hold that people understand and categorize concepts in terms of implicit theories, or general ideas they have regarding those concepts.

For example, what makes a GOOD SPORT?

In the PROTOTYPE VIEW, you would try to find characteristic features of a good sport.

In the COMPONENTIAL VIEW, you would try to isolate features of a good sport.

In the EXAMPLAR VIEW, you might try to find some good examples you have known in your life.

In the theory-based view, you would use your experience to construct an explanation for what makes someone a good

sport.

SO what does it means to be a GOOD SPORT in a theory-based view?

A good sport is someone who, when he or she wins, is gracious in victory and dos not mock losers or otherwise make them feel bad about losing. It is also someone who, when he or she loses, loses graciously and does not blame the

winner, the referee, or find excuses. Rather, he or she takes the defeat in stride, congratulates the

winner, and then moves on.

FINDING THE “ESSENCE” OF THINGS

SEMANTIC-NETWORK MODELS

Semantic Network Models suggests that knowledge is represented in our minds in the

form of concepts that are connected with each other in a web-like form

Collins and Quillan’s Network ModelsKnowledge is represented in terms of hierarchal

semantic network.

A SEMANTIC NETWORK is a web of elements of meaning (nodes) that are connected with

each other through links.

ORGANIZED KNOWLEDGE representation takes the form of a hierarchal tree diagram. The elements are called nodes they are typically concepts.

The connections between the nodes are labeled relationships. They may indicate category membership, attributes, or some other semantic relationship. Thus a network provides a means of organizing concepts.

INHERITANCE

This concept implies that lower-level items inherit the properties of higher-level items.

Whatever was known about items at higher levels in a

hierarchy was applied to all items at lower levels in the

hierarchy

COMPARISON OF SEMANTIC FEATURES

Knowledge is organized based on a comparison of semantic features, rather than on a strict hierarchy of concepts

SCHEMATIC REPRESENTATIONS

SCHEMA SCRIPT

ORGANIZATIONOF

PROCEDURAL KNOWLEDGE

ORGANIZATION OF PROCEDURAL KNOWLEDGE

PROCEDURAL KNOWLEDGE REPRESENTATION

- acquired to practicing the implementation of a procedure

Psychologists have developed a variety of models for how procedural information is processed. Each

of the models involves:

SERIAL PROCESSING of information

in which information handled through a linear sequence of

operations, one operation at a time

One way in which computer can represent and organize procedural knowledge is in the form of set of rules governing a

PRODUCTION which includes the generation and output of procedure

In the same way computer simulation of production follow production rules, people may use the same

form of organizing knowledge of very close to it this production rules is the:

“if-then” rulesThe “if” clause includes a set of conditions that must be met to implement the “then’ clause.

The “then” clause is an action or a series of actions that are a response to “if” clause.

When the rules are described precisely and all the relevant conditions and actions are noted, a huge number of rules are required to perform even a very simple task.

These rules are organized into a structure of

ROUTINES SUBROUTINESinstructions regarding procedures for implementing a task.

Instructions for implementing a subtask within a larger task governed by a routine

Many of these routines and subroutines are

ITERATIVEthey are repeated many times during the

performance of a task

NONDECLARATIVE KNOWLEDGEknowledge traditionally has been has been described as either declarative

or procedural. One can expand the traditional distinction between declarative and procedural knowledge to suggest that NONDECLARATIVE KNOWLEDGE may encompass a broader range of mental representations

than just procedural knowledge.We mentally represent the following forms of non declarative knowledge:

PERCEPTAL, MOTOR, AND COGNITIVE SKILLS (procedural knowledge)

SIMPLE ASSOCIATIVE KNOWLEDGE (classical and operant conditioning)

SIMPLE NON-ASSOCIATIVE KNOWLEDGE (habituation and sensitization)

PRIMING

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The preceding example illustrate situations in which an item may prime another item that somehow related in meaning.

TWO TYPES OF PRIMING

SEMANTIC PRIMING REPITITION PRIMINGWe are primed a meaningful context or by meaningful information. Such information typically is a word or cue that meaningfully related to the target that is used.

A prior exposure to a word or other stimulus primes a subsequent retrieval of the information

INTEGRATIVE MODELS FOR

REPRESENTING DECLARATIVE AND

NONDECLARATIVE KNOWLEDGE

ADAPTIVE CONTROL of THOUGHT- RATIONAL (ACT-R)

PARALLEL PROCESSING: THE CONNECTIONIST MODEL

COMBINING REPRESENTATIONS: ACT-R (ADAPTIVE CONTROL OF THOUGHT- RATIONAL)

PROCEDURAL KNOWLEDGE

DECLARATIVE KNOWLEDGE

represented in the form of production systems

represented in the form of propositional networks

Proposition the smallest unit of knowledge that can be judged to either true or false

In ACT-R, networks include images of objects and corresponding spatial configurations and relationships. They also include TEMPORAL

INFORMATION, such as relationships involving the sequencing of actions, events, or even the

order in which items appear.

TEMPORAL INFORMATION = TEMPORAL STRINGS

they contain information about the relative time sequence

DECLARATIVE KNOWLEDGE within ACT-R

it contains a MECHANISM by which information can be retrieved and also a STRUCTURE for storing information.

within a semantic network, concepts are stored at various nodes within the network these nodes can be either inactive or active at a given time.

ACTIVE NODE - is one that is in a sense, "turned on".

a node can be turned on- activated- directly by external stimuli, such as sensations, or it can be activated by internal stimuli, such as memories or thought processes, and it can also be activated indirectly, by the activity of one or more neighboring nodes

there is SPREADING ACTIVATION within the network from one node to

another due to each nodes receptivity to stimulation from neighboring

nodes.

ACT-R also suggests means by which the network changes as a result of

activation. For one thing, the more often particular links between nodes are used,

the stronger the links become.

PROCEDURAL KNOWLEDGE within ACT-R

Such knowledge is represented in production systems rather than in semantic networks. Knowledge representation of procedural skill occurs in three stages:

COGNITIVE ASSOCIATIVE AUTONOMOUS

we think about explicit rules

for implementing the procedure

we consciously practice using the

explicit rules extensively,

usually in a highly consistent manner

is the overall process which we transform

slow, explicit information about

procedure ("knowing that") into speedy,

implicit, implementation of procedures ("knowing

how“)

COMPOSITIONa means by which we make this transformation.

PRODUCTION TUNINGanother aspect of proceduralization, it involves the two complementary processes of generalization and discrimination.

PARALLEL PROCESSING: THE CONNECTIONIST MODEL

Computer-inspired information-processing theories are processed one step after another. Some aspects of human cognition may indeed be explained in terms of serial processing, but psychological findings and other cognitive research seem to indicate other aspects of human cognition.

Parallel Processing

multiple operations can go all at once

PARALLEL DISTRIBUTED PROCESSING (PDP) MODELS or

CONNECTIONIST MODELS

states that we handle very large numbers of cognitive operations at once

through a network distributed across incalculable numbers of locations in the

HOW THE PDP MODEL WORKS

The mental structure which parallel processing is believed to occur is a network. In connectionist

networks, all forms of knowledge are represented within the network structure.

In the PDP model, the network comprises neuron-like units. They do not, in and of themselves, actually

represent the concepts, propositions, or any other type of information. Thus the pattern of connections

represents knowledge not the specific units.

Differing cognitive processes are handled by differing patterns of activation, rather than a result of a different

set of instructions from a computer’s central processing unit. In the brain, at any one time, a given

neuron may be :

INACTIVE EXCITATORY INHIBITORYneurons are

not stimulated beyond their threshold of excitation.

neurons release neurotransmitters

that stimulate receptive neurons at

the synapse.

neurons release neurotransmitters

that inhibit receptive neurons.

The more often a particular connection is activated, the greater is the strength of the connection, whether the connection is excitatory or inhibitory

According to the PDP model, whenever we use knowledge, we change our presentation of it.

Thus KNOWLEDGE REPRESENTATION is not really a final product

Rather, it is a process or even a potential process.

It is pattern of potential excitatory or inhibitory connection strengths.

When we receive new information, the activation from that information either:

STRENGTHENS WEAKENS

the connections between units

The ability to create new information by drawing inferences and making generalizations allows for almost

infinite versatility in knowledge and manipulation.

HUMAN MINDS ARE FLEXIBLE

This versatility allow as to accommodate incomplete and distorted information

By using the PDP model, cognitive psychologists attempt to explain various general characteristics of

human cognition.

CRITICISMS OF THE CONNECTIONIST MODEL

COMPARING CONNECTIONIST WITH NETWORK

REPRESENTATIONS

cognitive psychology report

categories concepts

organization of knowledge

categories feature

procedural knowledge

forms of knowledge

classic view of categories

basic level

subordinate level

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