1. Knowledge Representation and Organization
Chapter 8

2. Outline Organization of Declarative Knowledge
Concepts and Categories
Semantic Network Models
Schematic Representations
Representations of Procedural Knowledge
Integrative Models for Representing Declarative and Nondeclarative Knowledge
Combining Representations: ACT-R
Models Based on the Human Brain
Parallel Processing: The Connectionist Model

3. Which signature was more easily and accurately created?
As quickly and as legibly as possible, write your normal signature, from the first letter of your first name to the last letter of your last name.
Now as quickly and as legibly as possible, write your signature backward.
Which signature was more easily and accurately created?

4. Procedural Knowledge versus Declarative Knowledge
The what of knowledge representations
Procedural Knowledge
Involves some degree of skill, which increases as a result of practice
The how (the process) of knowledge representation
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For both signatures, you had available extensive declarative knowledge of which letters precede or followed one another, but for the first task, you also could call on procedural knowledge, based on years of knowing how to sign your name

5. 1. Organization of Declarative Knowledge
Concepts and Categories
Concept
Fundamental unit of symbolic knowledge
An idea about something that provides a means for understanding the world
Often a single concept may be captured in a single word
Category
One way to organize concepts
Functions to organize or point out aspects of equivalence among other concepts based on common features or similarity to a prototype

6. 1. Organization of Declarative Knowledge
Concepts and Categories
Feature-Based Categories: A Defining View
Classic view of conceptual knowledge involves disassembling a concept into a set of featural components, which are singly necessary and jointly sufficient to define the category
Defining features constitute the definition of a category, according to the feature-based, componential point of view
a defining feature is a necessary one: For a think to be an “X”, it must have that feature
E.g. Bachelor has defining features: male, unmarried, adult
This theory can not capture typicality within categories (e.g. robin versus penguin)

7. 1. Organization of Declarative Knowledge
1. Concepts and Categories
Prototype Theory: A Characteristic View
Suggests that categories are formed on the basis of characteristic features, which describe the typical model of the category
A prototype
The original item on which subsequent models are based
Model that best represents the class on which the category is based

8. 1. Organization of Declarative Knowledge
1. Concepts and Categories
Prototype Theory: A Characteristic View
Characteristic features
Whereas a defining feature is possessed by every instance of a category, a characteristic feature need not be
Many or most instances possess each characteristic features
e.g. the ability to fly is typical of birds, but it is not a defining feature of a bird (ostrich can not fly)

9. 1. Organization of Declarative Knowledge
1. Concepts and categories
Prototype Theory: A Characteristic View
Two kinds of categories:
Classical concepts
Categories that can be readily defined through defining features, such as bachelor
Inventions that experts have devised for labeling a class
Fuzzy concepts
Categories that cannot be so easily defined, largely because the borders of what constitutes them are fuzzy
Tend to evolve naturally (e.g. fruit)

10. apples, carrots, tomatoes, cauliflower, oranges, pumpkin, cucumber?
Divide the following items into the category of fruits and the category of vegetables:
apples, carrots, tomatoes, cauliflower, oranges, pumpkin, cucumber

11. 1. Organization of Declarative Knowledge
2. Semantic Network Models
Knowledge is represented in terms of a hierarchical semantic network
A web of interconnected elements consisting of
Nodes - The elements representing concepts
Labeled relationships which might involve category membership, attributes, or some other semantic relationship

12. 1. Organization of Declarative Knowledge
2. Semantic Network Models
Concepts appear to have a basic level of specificity within a hierarchy that is preferred to other levels (Eleanor Rosh, 1978)
The basic level is neither the most abstract nor the most specific (e.g. apple)
The basic level can be manipulated by context and expertise
Basic level is the one that has the largest number of distinctive features, which set it off from other concepts at the same level

13. 1. Organization of Declarative Knowledge
3. Schematic Representations
Schemas
A mental framework organizing knowledge, creating a meaningful structure of related concepts
Explain who concepts are related in the mind
E.g. kitchen

14. 1. Organization of Declarative Knowledge
3. Schematic Representations
Scripts
A structure that describes appropriate sequences of events in a particular context
Scripts include default values for the actors, the props, the setting, and the sequence of events
E.g. the restaurant script
Props – tables, a menu, a food
Roles to be played – a customer, a waiter, a cook
Opening conditions for the script – the customer is hungry and has money
Scenes – entering, ordering, eating, exhibiting
Results – customer has less money, the owner has more money

15. 2. Representations of Procedural Knowledge
Procedural knowledge can be organized in the form of sets of rules governing a production (generation and output of a procedure)
These rules are organized into
Routines
Instructions regarding procedures for implementing a task
Subroutines
Instructions for implementing a subtask within a larger task governed by a routine

16. 2. Representations of Procedural Knowledge
Production system
comprises the entire set of rules for executing the task or using the skill
E.g. a production system for a pedestrian to cross the street at an intersection with a traffic light
Traffic-light red  stop
Traffic-light green  move
Move and left foot on pavement  step with right foot
Move and right foot on pavement  step with left foot

17. 3. Integrative Models for Representing Declarative and Nondeclarative Knowledge
Combining Representations: ACT-R (Anderson)
Adaptive control of thought model of knowledge representation and information processing
A model of information processing that integrates a network representation for declarative knowledge and a production-system representation for procedural knowledge
Declarative network includes storing and retrieving of information; Procedural system implements the processes of proceduralization (automatization)

18. 3. Integrative Models for Representing Declarative and Nondeclarative Knowledge
Models based on human brain
Nondeclarative knowledge may encompass a broader range of mental representation than just procedural knowledge
Perceptual, motor, and cognitive skills
Simple associative knowledge (conditioning)
Simple nonassociative knowledge (habituation)
priming

19. 3. Integrative Models for Representing Declarative and Nondeclarative Knowledge
Models based on human brain
Amnesic patients:
Patient who is given repeated practice in reading mirror writing will improve as a result of practice but will not recall ever having engaged in practice
As your explicit access to nondeclarative knowledge decreases, your speed and ease of gaining implicit access to that knowledge increases

20. 3. Integrative Models for Representing Declarative and Nondeclarative Knowledge
Parallel Processing: The connectionist model
Parallel processing – multiple operations go on all at once
Parallel distributed processing (PDP) models or connectionist models
We may be able to process information as efficiently as we do because we can handle very large numbers of cognitive operations at once through a distributed network

21. 3. Integrative Models for Representing Declarative and Nondeclarative Knowledge
Parallel Processing: The connectionist model
Networks consist of nodes and connections between them
The more often a particular connection is activated, the greater is the strength of the connection
The basic aspect of these models is learning

22. 3. Integrative Models for Representing Declarative and Nondeclarative Knowledge
Domain general versus Domain specific systems
Domain general
The same mental processes underlie various cognitive tasks
Domain specific
There are specific mental processes underlying various cognitive tasks