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Saturday, December 27, 2014

Representation of knowledge, Prototype Theory, Schemas, Scripts, ACT-R Model, Squire’s Non-declarative Knowledge, PDP Model

Representation of knowledge
Knowledge representation promote exploration of a wide range of phenomena and offer the strength of converging operationsthe use of multiple approaches and techniques to address a problem. The way in which knowledge is represented profoundly influences how effectively knowledge can be manipulated for performing any number of cognitive tasks.
The fundamental unit of symbolic knowledge is the conceptan idea about something that provides a means of understanding the world. One way to organize them is by means of categories. A 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 all similar to a certain prototype.

·      Categories
·      Prototypes
·      Schemas
·      Scripts
·      Acquisition of declarative & procedural knowledge

Earlier models were based on behaviorist theory. “ Stimulus-response association theory was proposed by Clark Hull (1920). He argued that we learn to associate a particular response (the concept) with a variety of stimuli that define the concept.”
Jerome Bruner formulated a concept formation theory that involved cognitive processes, i.e. hypothesis testing about a concept by making guesses about which attributes are essential for defining the concept. Concept attainment according to Bruner et al. 1967:233) is "the search for and listing of attributes that can be used to distinguish exemplars from nonexemplars of various categories"
Eleanor Rosch (1978) suggested that the natural concepts in everyday life are learned through examples rather than abstract rules.
Anderson's Adaptive Control of Thought (ACT) theory suggests that long-term memory is an interconnect network of propositions (facts of concepts). Only a subset of interconnected propositions can be activated and more connected propositions are easier to retrieve. A concept that has many connections is elaborated.
“ Tennyson & Cocchiarella (1986) suggest a model for concept teaching that has three stages: (1) establishing a connection in memory between the concept to be learned and existing knowledge, (2) improving the formation of concepts in terms of relations, and (3) facilitating the development of classification rules. This model acknowledges the declarative and procedural aspects of cognition.”
“ Klausmeier (1974) suggests four levels of concept learning: (1) concrete - recall of critical attributes, (2) identity - recall of examples, (3) classification - generalizing to new examples, and (4) formalization - discriminating new instances.”

Using Our Minds
        Knowing that…Declarative knowledge
        Knowing how…Procedural knowledge
Declarative Knowledge
         Stored in Concepts
        A mental representation of an item and associated knowledge and beliefs (cat, tools, furniture)
When Do We Use Concepts?
         Create categories
         Make inferences
         Combine to form complex thoughts
         For communication
Organizing Structures of Declarative Knowledge
         Concept  --Unit of symbolic knowledge
         Category  --Rule used to organize concepts
         Schemas -- Framework used to organize concepts

Different Types of Concepts
         Natural Concept
        Occur naturally (e.g. plants, trees, cats)
         Artifact Concept
        Created by humans (e.g., hammers, computers)
         Ad Hoc Concepts
        Created individually to suit a need (things you need to be happy, things you do to please parents)
Different Theories on Concept Organization
         Defining Features (Classical View)
         Hierarchically semantic networks

Categorization and Concepts
o  Basic cognitive function is to categorize
n  Use experience to aid in future behavior and decision-making
o  Cognitive economy
o  Concepts
n  Mental representation of a category serving multiple functions
Functions of Concepts
o  Classification
n  Determine category membership
o  Understanding, making predictions, inference
n  Once classified one can then understand its relevant parts, know how to interact with it, infer other properties
o  Explanation and Reasoning
n  For example, of others’ behavior
o  Learning
n  New entities compared to and understood in terms of old and provide feedback for modification
o  Communication
n  Shared concepts and categorization allow for easier expression of ideas to others
o  Categories
n  Collection of objects, attributes, or actions, etc.
o  List of concepts
o  Hierarchy
n  Set of entities or examples picked out by the concept
o  How is experience distilled? How are functional relations established?
n  Category learning
o  How is knowledge represented in a category?
n  Structure
n  Schema
o  General knowledge structure that integrates objects, attributes, and actions into a cohesive representation
n  Script
n  Sequence
o  How do we use categorical knowledge?
o  Determining the category membership of various things (objects, properties, abstractions etc.)
o  Allows for treating otherwise discriminable entities as similar
n  Similarity as the organizing principle for categories and categorization
Types of Categories
n  Abstract vs. Concrete
o  Love vs. Mammal
n  Hierarchical vs. Non
o  Mammal vs. woman
n  Feature-Based Categories: A Defining View 
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 (or necessary attributes):  For a thing to be an X, it must have that feature. Otherwise, it is not an X.

Ex. Bachelor (male, unmarried, adult)  The features are each single necessary.  If one feature is absent, the object cannot belong to the category.  The three features are jointly sufficient.  If a person has all three features, then he is automatically a bachelor.

Prototype Theory: A Characteristic View  Prototype Theory – grouping of things together not by their defining features but rather by their similarity to an averaged model of the category.  Prototype is an abstract average of all objects in the category we have encountered before.  Crucial are characteristic features, which describe (characterize or typify) the prototype but are not necessary for it. They are commonly present in typical examples of concepts, but they are not always present.
Ex. Prototype of a game Prototype of a bird (robin or ostrich)  Whereas a defining feature is shared by every single object in a category, a characteristic feature need not be.
Classical concepts are categories that can be readily defined through defining features, such as bachelor.  Fuzzy concepts are categories that cannot be so easily defined, such as game or death.
Exemplars are typical representatives of a category.  Ex. Birds, we might think not only of the prototypical songbird, which is small, flies, builds nest, sings, and so on. We also might think of exemplars for birds of prey, for large flightless birds, for medium-sized waterfowl, and so on.

         Schemas are models of the external world based on past experience
         Schemas for concepts underlying situations, events, or sequences of actions
         Abstraction that allows particular objects or events to be assigned to general categories
         Organize our knowledge
         May include other schemas
         Help in encoding, storage, and recall
         Allows us to make inferences

Schemas – mental framework for organizing knowledge. It creates a meaningful structure of related concepts.
 A cognitive structure that organizes related concepts and integrates past events.  Ex. Kitchen (tells us the kind of things we might find in a kitchen and where we might find them)
Schemas have several characteristics that ensure wide flexibility in their use.  Schemas can include other schemas. Ex. A schema for animals includes a schema for cows, a schema for apes, and so on.  Schemas encompass typical, general facts that can vary slightly from one specific instance to another.  Schemas can vary in their degree of abstraction.

         Type of schema about events
         Structure captures general information about routine events
        Eating in a restaurant, attending a movie, a visiting a doctor’s office
         Scripts have typical roles
        (Customers, waiter, cook), (ticket vendor, patrons, refreshments), (doctor, nurse, patient)
         When we hear or read about a scripted event, our knowledge of the entire script is activated
         We can fill in or infer the scenes and actions that are not explicitly mentioned

Script contains information about the particular order in which things occur.  Ex. Restaurant script (coffee shop)  Props: tables, a menu, food, a check, and money  Roles to be played: a customer, a waiter, a cook, a cashier, and an owner.  Opening conditions for the script: the customer is hungry, and he or she has money  Scenes: entering, ordering, eating, and exiting  A set of results: the customer has less money; the owner has more money; the customer is no longer hungry; and sometimes the customer and the owner are pleased.

Jargon – specialized vocabulary commonly used within a group, such as a profession or a trade.  Imaging studies reveal that the frontal and parietal lobes are involved in the generation of scripts. The generation of scripts requires a great deal of working memory. Further script generation involves the use of both temporal and spatial information.
Scripts enable us to use a mental framework for acting in certain situations when we must fill in apparent gaps within a given context.

Acquisition of declarative & procedural knowledge
Representing Procedural Knowledge
         Serial Processing
        Linear sequence of operations
        Create using production rules
         If – then rules
        If sliding on ice then pump the brakes
         Tasks may take multiple rules
        Organized into routines and subroutines
ACT-R Model
         Combines declarative and procedural knowledge in a model
         Declarative knowledge is represented in structures called chunks defined by its type and slots
        Type represents concepts or categories (e.g., dogs) and slots as category attributes (e.g., color or size)
         Anderson (1980)
        Cognitive Stage
         Consciously think about steps to complete task
        Associative Stage
         Practice the procedure
        Autonomous Stage
         Skill has become automatic
Squire’s Non-declarative Knowledge
         Procedural knowledge
         Associative conditioning
        Classical and operant conditioning
         Simple nonassociative knowledge

Support for Squire’s Taxonomy
         Basil Ganglia damage
         Examine Parkinson’s and early Huntington disease patients
         No apparent amnesia (declarative memory intact)
         Problems with procedural memory
        Perceptual motor learning
        Habits & skills
         Just one example of variety of studies with humans and animals have supported Squire’s taxonomy

Two Types of Priming
         Semantic priming
        Meaning is primed
        Remember Nurse-Doctor study?
         Repetition priming
        Prior exposure primes same items seen later

Connectionist Model
         Parallel processing
        Multiple operations occur simultaneously
         Parallel Distributed Processing (PDP) models
        Goal is to model information as it is represented in the brain

The PDP Model
         The representation of information is distributed
         Knowledge for specific things are not stored explicitly, but stored in the activations of patterns among units 
         Learning occurs with changes in connection strength by experience
         Units send excitatory and inhibitory signals to other unit

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