This presentation is devoted rather briefly to various techniques used to represent knowledge in expert systems. We will first define the goal of Knowledge Representation. Before moving on to discuss concepts such as Artificial Intelligence agents and logic as a KR formalism

1. 1
Knowledge Representation and key
concepts
Harmony Kwawu
hkwawu@aol.com1
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Knowledge
Representation
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3
Compare and contrast various knowledge representation
techniques
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Knowledge Representation Formalism
Definition and brief explanation
Categories of Representation Formalism
Logic
Simple Proposition Logic
Simple Predicate Logic
Production Rule
Semantic Network
Frames and Frame hierarchy
Selecting KR Formalism for your project
Key points to take away
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5
Intelligent behaviour is not so much about method of
reasoning but the amount of knowledge available to reason
with.
Human experts and computer agents need access to
information and knowledge in order to reach reasoned
decision, form judgement or solve a problem.
In computing and expert systems in particular, deciding
on the right way to organise information so that it’s easy
for a system to access and use when needed can be
tricky but essential
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This presentation is devoted rather briefly to various techniques
used to represent knowledge in expert systems. We will first define
the goal of Knowledge Representation (KR).
This is followed with a quick discussion of concepts such as
Artificial Intelligence agents and logic as a KR formalism.
In a previous slide (key expert system concepts) we explored rule
base knowledge representation. In this follow on, we examine
Proposition logic and First order predicate logic as ways of
organising knowledge in expert systems.
We conclude by encouraging the reader to test their knowledge by
completing the end of text quiz
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2. 7
The Goal of Knoweldge Representation
techniques
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The purpose of knowledge representation is to ensure expert system
agents have access to the knowledge (combination of relevant facts
and rules) they need to reason and reach conclusion
Knowledge representation is an active part of knowledge base
systems and AI Applications development
It is dedicated to presenting information in a form that a computer
agent can access, understand and use.
knowledge in expert system can be represented in many different
ways to satisfy different knowledge requirements, format and
problem domains
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9
Working
memory
Knowledge
base
Interface
Engine
Experts Knowledge Engineer Developer
End user
With computer
& interface
Receives
expert advice
Ask question
or query
9 10
What is meant by Artificial Intelligence
Agent?
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An artificial intelligence agents (like software Robots, chat
bots etc) are a special purpose computer application
designed to serve a particular purpose or provide a distinct
service.
Examples are; web crawlers in search engines, chat bots
(SIRI & Cortana ), business analytics Bots (Cortana
intelligence) etc
They are generally autonomous and acts in collaboration
with other agents or compete with other agents for
computer resources
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I. What is knowledge in
knowledge base?
II. Is knowledge the same as
fact or information?
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3. 13
Logic as a Knowledge Representation
formalism
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Logic is broadly defined as the area of science dedicated to
understanding methods for evaluating reasoned arguments.
Put simply, logic is the school of thought devoted to assessing
valid reasoning.
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Logic is an important and useful tool when evaluating
argument and reasoning.
Without logic, it would be difficult if not impossible to evaluate
the soundness or validity of an argument
Reason, not instinct is the guiding principle for all rational
human beings, so say the philosophers
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Human
Doctor?
Mycin Expert
System
OR
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Logical Argument
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Generally, an argument is made up of two parts: Making a
proposition and drawing conclusion from it
Note that a proposition is an expression or statement that can
be believed, or is either true or false (www.merriam-
webster.com)
For example: I propose that all human beings are created
equal. This statement is open to agreement or rejection after
careful consideration
Either way, the fact that the statement above has an
expression and a possible outcome makes it a valid argument
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4. 19
The value of logic is more than a tool for verifying lines of
reasoning
Logic offers an effective way to organise knowledge
In computing for example, principles of logic are used to
design electronic circuits board and for representing
knowledge in intelligent systems such as AI Technologies
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Logic can be expressed in many different forms depending
on complexity of the situation and application environment.
Examples of logic used in representing knowledge in AI
applications are:
Proposition logic
First order predicate logic
Fuzzy logic
Both Proposition logic and First order predicate logic are
briefly discussed below
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Proposition Logic
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Often humans generally and experts in particular makes
statements that may turn out to be true or false.
Statement of truth or false as we have learned previously is
called proposition
A single proposition can be true and not false at the same
time.
Confusing, you are not along. It get clearer over time
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To recap recall that concept describing proposition and conclusion
statement is known as proposition logic.
Proposition logic is therefore a statement of truth or false and
possible outcome
This can be illustrated as below:
Proposition or
expression
Evaluate
Outcome
Outcome
Y
N
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The following statements are propositions
1)James put in a lot more effort in her studies than most
students.
1b)Conclusion: He achieve high grade in all his exams
2)All priests are kind and loving
2b)conclusion: Count Dracula is a priest
3)Mothers are more protective of their children than fathers
3b)conclusion: Maria is a mother because she is protective of
her children
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5. 25
Each set of the above propositions can be expressed in
proposition logic as follow:
If James puts in a lot more effort in his studies than most
THEN James will achieve high grade in all her exams
IF Count Dracula is a priest THEN Count Dracula is kind
and loving
Mothers are more protective of their children than fathers
this IMPLIES that Maria is more protective of her children
than their father
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Rules of logical inference for
compound proposition
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27
Two or more propositions can be combined to form a chain
of statements using what is known as connectives
Examples of connectives are: AND, OR, NOT and
IMPLICATION
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Negation NOT {e.g. X is true if the proposition is false}
Conjunction AND {e.g. only true if all possible propositions
are true}
Disjunction OR {e.g. only true if one of the proposition is
true}
Implication {this depends on what the proposition implies. If
a proposition implies another is true or false then that is
considered to be the case.}
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29
Truth Table as proposition evaluate tool and
more
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Truth Tables are generally used to evaluate compound
proposition.
They can be used to produce possible combinations of all
truth values of basic propositions.
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6. 31
Try to workout and complete the truth table in
the slide below
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The truth table below is for evaluating loan decision for bank
customers: copy and use your own knowledge from previous
class discussions to complete the table
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The rule of Inference
Bank
customer
(B)
Has
good
credit
record
(G)
Negation
(NOT)
Conjunction
(AND)
Disjunction
(OR)
Implication
(any thing
goes
inference)
T T
T F
F T
F F
See the end of slide for solution
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How did you do: show your answer to and
discuss it with a friend
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Application of Proposition Logic
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Proposition logic can be used in implementing the following:
Translation of business rules
Implementing Rule Based Expert Systems
Design of logic gates circuit board for computing devices
Any more? Please add your own example to extend the list
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7. 37
Basic Predicate Logic as another form of
KR Techniques
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While it’s possible to make a number of compound
statements using proposition logic, it’s often difficult to apply
it to more complex situations
Proposition logic is not appropriate for expressing and
representing assertions in fields such as mathematics and
physics
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To overcome this limitation, a new type of logic was
introduced. This is known as predicate logic
Detail discussion of predicate logic is beyond the scope of this
module, we would therefore limit ourselves to basic definition
and application of it
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Predicate logic provides formalism for performing a more
complex analysis of proposition and additional methods for
reasoning with quantified expressions.
Predicate logic allow proposition to be broken into
components.
The two main components are: argument and predicates.
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It can be used to represent and evaluate statements such as:
X is Equivalence to Y
6 is greater than 4
M is Less than K, etc
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Predicates are verbs or action phrases that describes a
property of objects, events or a relationship.
Object in predicate logic are represented by variables.
Predicate may be used to illustrate actions or relationship
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8. 43
Predicate and proposition logic difference
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Compared to proposition logic, which can only be used to
make simple true or false statements, predicate logics are
more expressive.
In addition to the connectives used in propositional logic,
predicate logic also uses variables, constants, action phrases
(predicates) and universal qualifiers to make more
expressive proposition statements.
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Universal quantifiers in proposition logic are used when
making general inference about objects. For example, when
referring to all objects in a population.
Such as all our student are male
This is detonated by the symbol (for all) and existential
quantifiers (for one object) out of many
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The following statement, “Every one of our students comes
from UK”
• This is interpreted as: for any object y, if y is a student, THEN y
comes from UK
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Identify the subjects and predicates in the statement
below:
All students goes to college 5 days in a week
Michael is a Nigerian male and drives a Green car
All the men from UK are very tall
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Other knowledge representation formalisms include:
Rules base knowledge represntation,
Semantics network, and
Frames
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9. 49
What is Semantic Network Anyway?
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Semantic network, also known as concept network is any such
formalism which aims to capture and express meaning (semantics)
in a graphical form.
Semantics network could be used for propositional atomic
information analysis.
A proposition is always true or false and is called atomic because
the truth value in such a proposition can not be further divided
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Semantic network consists of nodes and arch connecting them.
Nodes are objects and arches are used to describe links between
nodes.
The links are used to express relationship between the nodes and
dependencies
One major strength of semantic network is that it can be used to
represent how humans store and manipulate knowledge
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Semantic network was originally designed to represent human
memory and understanding
It can be used to:
Workout common interest among a group of customers,
household, group of students etc
Determining the difference between people, their age,
occupation, education and other related properties
Areas of application include:
Search engines
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Hospital
Patient
Female
Patient
Male
Patient
Osy Stella
Edward Mary Afume
Is the husband of
Is the son of Is mother of
Lives at the
same address
Is a Is a
Is a Is a
Is the doctor of
Hospital patient
semantic network
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Expert Systems Frame
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10. 55
Frame knowledge representation formalisms are used for
information that are multi-faceted and hierarchical
This is similar to how data is described, structured and stored in
object oriented or enhanced entity relational databases.
Data or information fields in frames are known as slots and values
stored in the slots are known as fillers
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Student Frame
Course
Lecturer:
SName:
SContact:
Type:
Course level:
Lecturer Frame
Specialism
Lecturername:
Assignments:
SContact:
Research Interest
Course level:
Student and lecturer Frame
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Each slot in a frame contain information in various representations,
including logical sentences and production rules.
A slot in frames can also contain another frame, to form a
hierarchical relationship.
Each frame represents object or situation and can be accessed by
the inference engine
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Student
Frame
Hierarchy
PartTime Student
academic Grade
Frame
International FullTime
Student Frame
PartTime student
address Frame
Home FullTime
Student Frame
FullTime student
address frame
Frame Hierarchy
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Frame are used to arrange knowledge about objects,
situations, events and their associations for expert systems
Frame as knowledge representation formalism can store
information about an object, events as well as any methods
and procedural associated with them
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KR is using different methods to organise informatiion and
presenting it in a way that is accessible to the inference
engine of expert system
Where knowledge is presented according to the the problem
the system is designed to solve
Knoweldge in Expert System can be presented as Rules,
Semantics network, Logic or Frames
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11. 61
What is knowledge representation?
Why are there different knowledge representation
techniques and system?
Which one is best and why?
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Fuzzy logic and Expert system Project ideas and
challenges
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The rule of inference
Bank
custome
r (B)
Has
good
credit
record
(G)
Negation
(NOT)
Conjunction
(AND)
Disjunction
(OR)
Implication
(any thing
goes
inference)
T T F T T T
T F F F T F
F T F F T T
F F T F F T
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To find out more, logon to the web site below:
http://groups.csail.mit.edu/medg/ftp/psz/k-rep.html
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END
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