Cognitive psychology Chapter 8 REV PDF

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CHAPTER 8: THE ORGANIZATION OF KNOWLEDGEIN THE MINDCONVERGING OPERATIONS-the use of multiple approaches and techniques to address a problem --the way in w/c knowledge is represented profoundly influences how effectively knowledge can be manipulated for performing any number of cognitive task Ex: CML...

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CHAPTER 8: THE ORGANIZATION OF KNOWLEDGE IN THE MIND CONVERGING OPERATIONS -the use of multiple approaches and techniques to address a problem --the way in w/c knowledge is represented profoundly influences how effectively knowledge can be manipulated for performing any number of cognitive task Ex: CMLIX 959 x LVIII x 58 ORGANIZATION OF DECLARATIVE KNOWLEDGE CONCEPT -an idea about something that provides a means of understanding the world. --a fundamental unit of symbolic knowledge, or knowledge of correspondence between symbols and their meaning. Ex. The symbol “3” means “three” CATEGORY -hierarchy of concepts Ex. bird is a concept but also a category (robin,hawk etc as its members) --that is, a category is a group of items into w/c different objects or particular concepts can be placed that belong together because they share some common features, or because they are all similar to a certain prototype. Ex. So a “bird” is a concept, but it also is a category that includes, at more specific level of the hierarchy (robin, hawk, etc). at more general level of the hierarchy, a bird is a kind of animal. CONCEPT AND CATEGORIES NATURAL CATEGORIES -are groupings that occur naturally in the world. (birds, trees, etc.) ARTIFACT CATEGORIES -are groupings that are designed or invented by humans to serve particular purposes or functions (automobiles, & kitchen appliances) --the speed it takes to assign objects to categories seems to be about the same for both natural and artifact categories ad hoc categories- categories created to achieve goals in everyday life or for specific purposes --typically are described ot in words but raher in phrases. (their content varies depending on the context) ex. “my bestfriends”, things one can write on”, “things I need to purchase in the market” ---concepts, in general, and categories in particular are also used in other areas like computer science. *Categories appear to have basic level (natural level) of specificity; a level w/n the hierarchy that is preferred to other levels. -the basic level is the one that most people find to be maximally distinctive. -when people are shown pictures of objects, they identify the objects at a basic level more quickly than they identify objects at a basic level more

quickly than they identify objects at higher or lower levels. *superordinate level- a “fruit” *basic level- an “apple” *subordinate level- “a red delicious apple” FEATURE-BASED CONCEPTS: DEFINING VIEW -the classic vie of concepts disassembles a concept into a set of featural components. All those features are the necessary to define the concept. DEFINING CONCEPTS (necessary attributes) -features uniquely define the concepts Ex. “BACHELOR”----must be male, unmarried, adult If one feature is absent, the object cannot belong to the category --according to this view, you cannot be male, unmarried and adult, and at the same time not be a “bachelor” --but some concepts do not readily lend themselves to featural analysis. Ex. “GAME” finding anything at all that is a common feature of all games is actually difficult to do (some are “fun” some “are not” *Wittgenstein- suggested that we know what is game by means of family resemblance ----thus, a “game” is concept whose category members share features, but w/o any particular feature being common to all members. *FEATURE-BASED THEORY, in sum, has some attractive features, but it does not give a complete account of concepts or categories. PROTOTYPE THEORY: A CHARACTERISTIC VIEW PROTOTYPE THEORY -grouping things together not by their defining features rather by their similarity to an averaged model of the category. PROTOTYPE -an abstract average of all the objects in the category we previously have encountered -that is, we have an average representation of the category, and we compare objects to that average representation (prototype) when making a decision whether or not to place them in a certain category. *objects that are prototypical of a category therefore have a high family resemblance. ---an object will be classified as belonging to a category if it is sufficiently similar to the prototype, that is if it has some family resemblance. CHARACTERISTIC FEATURES -crucial for prototypes; w/c describes (characterize or typify) the prototype but are not necessary for it. -commonly are present in typical examples of concepts, but they are not always present. Ex. When people are asked to list the features of a category such as “fruit” or “furniture”, most list features like “sweetness” or “made out of wood”. –these features are characteristic rather than defining

--this matters in our interactions w/ other people as well: stereotypes of different groups of people (Italians or psychologists) consist of conglomerate of average features. CLASSICAL AND FUZZY CONCEPTS CLASSICAL CONCEPTS -categories that can be readily defined through defining features, such as “bachelor” -tend to be inventions that experts have devised for arbitrarily labeling a class that has associated defining features. --classical concepts and categories may be built on defining features.

--consider the concept of a “robber”. The core requires that someone labeled as a robber be a person who takes things from others w/o permission. --the prototype, however, tends to identify particular people as more likely to be robbers. *researchers, tested the notion that we come to understand the importance of defining features only as we grow older -the younger children viewed someone as a robber even if the person did not steal anything. What mattered was the that the person had the characteristic features of a robber. THEORY-BASED VIEW OF CATEGORIZATION

FUZZY CONCEPTS -categories that cannot be so easily defined, such as “game” or “death”. -tend to evolve naturally --fuzzy concepts and categories are built around prototypes *for our purposes, we view similarity in terms of the number of features shared between an object and the prototype. Perhaps some features even should be weighed more heavily as being more central to the prototype than are other features. REAL-WORLD EXAMPLES: USING EXEMPLARS EXEMPLARS -typical representatives of a category. --categories are setup by creating a rule and then by storing examples of exemplars. Objects are then compared to the exemplars to decide whether or not they belong in the category the exemplars represent. *exemplar theories of categorization also has been “criticized”. One notable criticism questions the number of exemplars and types of exemplars that are stored for each category. Some theorists contend that the mind does not have enough resources to store all the exemplars one would need to typify membership in a category. VARYING ABSTRACTION MODEL (VAM) -suggest that prototypes and exemplars are just two extremes on a continuum of abstraction. -most of the time we do not use just one abstract prototype or a large number of concrete exemplars for categorization. Instead we use a number of intermediate representations that represent subgroups w/n the category Ex. Animals might be represented by specific exemplars of kinds of animals, such as “finch” or “sparrow” or “whale”, but also by higher order categories such as “songbird” or “marine mammal” A SYNTHESIS: COMBINING FEAUTURE-BASED AND PROTOTYPE THEORIES -full theory of categorization can combine both defining and characteristic features, so that each category has both a prototype and a core. CORE- the defining feature something must have to be considered an example of a category.

How Do People Use Their theories for Categorization? THEORY-BASED VIEW OF MEANING -holds that people understand and categorize concepts in terms of implicit theories, or general ideas they have regarding those concepts. Ex. What makes someone a “good sport”? Feature-based view Prototype view

You would try to isolate features of a good sport You would try to find characteristic features of a good sport Exemplar view You might try to find some good examples in your life Theory-based view Use experience to construct an explanation for what makes someone a good sport --A “good sport” is someone who when he or she wins, is gracious in victory and does not mock losers or otherwise make them feel bad about losing *in the theory-based view, it is difficult to capture the essence of the theory in a word or two, rather, the view of a concept is more complex *suggests that people can distinguish between essential and incidental, or accidental, features of concepts because they have complex mental representations of these concepts. (sorp & doon) FINDING THE “ESSENCE” OF THINGS ESSENTIALISM -this view holds that certain categories, such as those of “lion” or “female”. Have an underlying reality that cannot be observed directly.

SEMANTIC NETWORK MODELS -suggests that knowledge is represented in our minds in the form of concepts that are connected w/ each other in a web-like form. *COLLINS & QUILLIAN’S NETWORK MODEL HIERARCHICAL SEMANTIC (related to meaning as expressed in language—linguistic symbols) -a semantic network is a web of elements of meaning (nodes) in w/c the elements are connected w/ each other through links.

--organized knowledge representation takes the form of hierarchical tree diagram. NODE- the elements; typically concepts. LABELED RELATIONSHIP- connections between the nodes (might indicate category, membership, attributes or semantic relationships. --thus a network provides a means for organizing concepts. The exact form of a semantic network differs from one theory to another, but most networks look something like the highly simplified network. COMPARING SEMANTIC FEATURES -an alter theory is that knowledge is organized based on a comparison of semantic features, rather than on a strict hierarchy of concepts -- (sound similar but different to feature-based theory of categorization)-features of different concepts are compared directly, rather than serving as the basis for forming category. --word stem completion (s_ _ m)- the activation of one node of the network increases the activation of related nodes *we may broaden our understanding of concepts further if we consider not only the hierarchical and basic levels of a concept, but also other relational information the concept contains. SCHEMATIC REPRESENTATION SCHEMAS -one main approach to understanding how concepts are related in the mind. *schema- mental framework for organizing knowledge - it creates a meaningful structure of related concepts Schemas have several characteristics that ensure wide flexibility in their use. 1.

Schemas can include other schemas (schema for animal, includes schema for cows, apes, etc) 2. Encompasses typical, general facts that can vary slightly from one specific instance to another. 3. Can vary in their degree of abstraction. (schema for “justice” is much more abstract than a schema for apple or even a schema for fruit.) Schemas also include information about relationships. *concepts (link between trucks and cars) *attributes w/n concepts (height and weight of an elephant) *attributes in related concepts ( the redness of a cherry and the redness of an apple) *concepts and particular contexts (fish and the ocean) *specific concepts and general background knowledge (concepts about particular U.S presidents and general knowledge about U.S government and about US history) *relationships w/n schemas particularly interest cognitive psychologists are causal (if-then) relationships. --Boundary extension

-contains information about the particular order in w/c things occur --in general scripts are much less flexible than schemas. However, it includes default values for actors, props, settings, and the sequence of events expected to occur. --frontal and parietal lobes area involved in the generation of scripts *typicality effect- when a person is learning a script, if both typical and atypical actions are provided, the atypical information will be recalled more readily. *scripts enables us to use mental framework for acting in certain situations when we must fill in apparent gaps w/n a given context. REPRESENTATION OF HOW WE DO THINGS: PROCEDURAL KNOWLEDGE THE “PRODUCTION OF PROCEDURAL KNOWLEDGE” Procedural knowledge representation - is acquired by practicing the implementation of procedure --once a mental representation of nondeclarative knowledge is constructed ( proceduralization is complete) that knowledge is implicit. (it is hard to make explicit by trying to put it in words. --practice often decreases explicit access to knowledge --as your explicit access to nondeclarative knowledge decreases, however, your speed and ease of gaining implicit access to that knowledge increases. -eventually, most nondeclarative knowledge can be retrieved for use much more quickly than declarative knowledge can be retrieved Serial processing- info is handled through a linear sequence of operations, one operation at a time. --psychologist have developed a variety of models for how procedural information is presented and processed each of these models involves serial processing. Production - includes the generation and output of procedure. (one way in w/c computers can represent and organize procedural knowledge. Production system -includes the entire set of rules (productions) for executing the task or using the skill. --used when you want to complete a particular task or use a skill. *sometimes, production system, like computer programs, contain bugs. Bugs- are flaws in the instructions for the conditions or for executing the actions. *according to the production model, human representations of procedural knowledge may contain some occasional bugs. NONDECLARATIVE KNOWLEDGE -may encompass a broader range of mental representations than just procedural knowledge

*a problem w/ schemas is that they can give rise to stereotypes

Procedural knowledge

SCRIPTS

Associative

Perceptual, motor, cognitive skills Classical and operant

knowledge(conditionin g) Nonassociative Priming

“temporal strings”-temporal information; contain info about the relative time sequence.

conditioning

Habituation and sensitization Fundamental links w/s a knowledge network, in w/c the activation of information along particular mental pathway facilitates the subsequent retrieval of info along a related pathway or even the same mental pathway *all of these nondeclarative forms of knowledge are usually implicit. (you are not aware of the different steps you carry out when you act, and it is hard for you spell them out explicitly) Semantic priming- we are primed by a meaningful context or by meaningful information. (such info typically is “word” or “cue” that is meaningfully related to the target that is used.) Repetition priming- prior exposure to a word or other stimulus primes a subsequent retrieval of that information. *according to the spreading activation theories, the amount of activation between a prime and a given target node is function of two things: -the number of links connecting the prime and the target -the relative strength of each connection. --this view holds that increasing the number of intervening links tends to decrease the likelihood of the priming effect. But increasing the strength of each link between the prime and its targets tends to increase the likelihood of the priming effect. *the occurrence of priming through spreading activations taken by most psychologists as support for network model of knowledge representation in memory processes.

COMBINING REPRESENTATIONS: ACT-R ACT (ADAPTIVE CONTROL OF THOUGHT) -model of knowledge representation and information processing. *John Anderson- in his model, he synthesized some of the features of serial information-processing models and some of the features of semantic-network models --in ACT, procedural knowledge is represented in the form of production systems. --declarative knowledge is represented in the form of propositional networks. Proposition- defined by Anderson, as being the smallest unit of knowledge that can be judged to be either true or false. ACT is evolved form of earlier models ACT-R (ADAPTIVE CONTROL OF THOUGHTRATIONAL) -model of information processing that integrates a network of representation for declarative knowledge and production system representation for procedural knowledge. --in the ACT-R, networks include images of objects and corresponding spatial configurations and relationships. --they also include temporal informations, such as relationships involving the sequencing of actions, events, or even the order in w/c items appear.

DECLARATIVE KNOWLEDGE W/N ACT-R -according to Anderson’s model, the nodes can be either inactive or active at a given time. SPREADING ACTIVATION -given each node’s receptivity to stimulations from the neighboring nodes, there is spreading activation w/n the network from one node to another. But the amount of info (number of nodes) that can be activated at any one time has limits. --as more nodes are activated and the speed of activation reaches greater distance from the initial source of activation, the activation weakens. *Therefore, the nodes closely related to the original node have a great deal of activation. However, nodes that are more remotely related are activated to a lesser degree. * the more often particular links between nodes are used, the stronger the links become. PROCEDURAL KNOWLEDGE W/N ACT-R Proceduralization -the overall process by w/c we transform slow, explicit info about procedures (knowing that) into speedy, implicit, implementation of procedures (knowing how) STAGES OF PROCEDURAL KNOWLEDGE COGNITIVE STAGE We think about explicit rules for implementing the procedures ASSOCIATIVE STAGE we consciously practice using the explicit rules extensively, usually in a highly consistent manner AUTONOMOUS STAGE we use these rues automatically and implicitly w/o thinking about them. We show a high degree of integration and coordination, as well as speed and accuracy.  The human brain seems to engage in multiple processes simultaneously. It acts on myriad bits of knowledge all at once. PARALLEL PROCESSING: THE CONNECTIONSIT MODEL Parallel Processing- It is the ability of the brain to make sense of several different incoming stimuli at the same time. •

A computer can respond to an input within a nanoseconds but an individual neuron may take up to 3 millisecond to respond

Parallel Distributed Processing Model •

According to this model, we handle large numbers of cognitive operations at once through a network from incalculable number of locations in the brain.

How Parallel Distributed Processing Model works? These interconnected patterns of nodes enable the individual to organize meaningfully the knowledge contained in the connections among the various nodes It is conceived as the strength of connection between the different neutral networks. In the brain in anytime, a given neuron may be Inactive neurons Inactive neurons are not stimulated beyond their threshold of excitation. They do not release any neuro transmitter into the synapse. Excitatory Neurons Excitatory Neurons release neurotransmitters that stimulate receptive neurons at the synapses. They increase the likelihood that the receiving neurons will reach their threshold of excitation. Inhibitory Neurons Inhibitory neurons release neuro transmitters that inhibit receptive neurons. They reduce the likelihood that the receiving neurons will reach their threshold of excitation.

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When we receive new information, the activation from the information either strengthens or weakens the connections between units. The new information may come from environmental stimuli, from the memory or cognitive process.

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By using PDP model cognitive psychologist attempt to explain various general characteristic of human cognition. These characters include our ability to respond flexibility, dynamically, rapidly and relatively accurately.

What is neural Network Model? A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operat...