Humans are best at understanding, reasoning, and interpreting knowledge.

Human knows
things, which is knowledge and as per their knowledge, they perform various actions in
the real world. However, how machines do all these things comes under knowledge
representation and reasoning. Hence, we can describe Knowledge representation as
following:

o Knowledge representation and reasoning (KR, KRR) is the part of Artificial

intelligence, which concerned with AI agents thinking and how thinking contributes
to intelligent behavior of agents.
o It is responsible for representing information about the real world so that a
computer can understand and can utilize this knowledge to solve the complex real
world problems such as diagnosis a medical condition or communicating with
humans in natural language.
o It is also a way, which describes how we can represent knowledge in artificial
intelligence. Knowledge representation is not just storing data into some database,
but it also enables an intelligent machine to learn from that knowledge and
experiences so that it can behave intelligently like a human.

What to Represent:

Following are the kind of knowledge which needs to be represented in AI systems:

o Object: All the facts about objects in our world domain. E.g., Guitars contains
strings, trumpets are brass instruments.
o Events: Events are the actions which occur in our world.
o Performance: It describe behavior, which involves knowledge about how to do
things.
o Meta-knowledge: It is knowledge about what we know.
o Facts: Facts are the truths about the real world and what we represent.
o Knowledge-Base: The central component of the knowledge-based agents is the
knowledge base. It is represented as KB. The Knowledgebase is a group of the
Sentences (Here, sentences are used as a technical term and not identical with the
English language).
Types of knowledge:

1. Declarative Knowledge:

o Declarative knowledge is to know about something.

o It includes concepts, facts, and objects.
o It is also called descriptive knowledge and expressed in declarative sentences.
o It is simpler than procedural language.

2. Structural knowledge:

o Structural knowledge is basic knowledge to problem-solving.

o It describes relationships between various concepts such as kind of, part of, and
grouping of something.
o It describes the relationship that exists between concepts or objects.

3. Procedural Knowledge

o It is also known as imperative knowledge.

o Procedural knowledge is a type of knowledge which is responsible for knowing
how to do something.
o It can be directly applied to any task.
o It includes rules, strategies, procedures, agendas, etc.
o Procedural knowledge depends on the task on which it can be applied.
4. Meta-knowledge:

o Knowledge about the other types of knowledge is called Meta-knowledge.

5. Heuristic knowledge:

o Heuristic knowledge is representing knowledge of some experts in a filed or

subject.
o Heuristic knowledge is rules of thumb based on previous experiences, awareness
of approaches, and which are good to work but not guaranteed.

There are mainly four ways of knowledge representation which are given as follows:

1. Logical Representation
2. Semantic Network Representation
3. Frame Representation
4. Production Rules

1. Logical Representation:

Logic can be represented via agreed-upon syntax and objects. It deals with the
prepositions and has no ambiguity in meaning or interpretation. This type of
representation can help in logical reasoning and have a better representation of facts.
However, logical representations can be tricky to work with. The strict rules of syntax and
associations may make the process tricky. Logical representation is a language with some
concrete rules which deals with propositions and has no ambiguity in representation.
Logical representation means drawing a conclusion based on various conditions. This
representation lays down some important communication rules. It consists of precisely
defined syntax and semantics which supports the sound inference. Each sentence can be
translated into logics using syntax and semantics.

Syntax:

o Syntaxes are the rules which decide how we can construct legal sentences in the
logic.
o It determines which symbol we can use in knowledge representation.
o How to write those symbols.

Semantics:

o Semantics are the rules by which we can interpret the sentence in the logic.
o Semantic also involves assigning a meaning to each sentence.

Logical representation can be categorized into mainly two logics:

 Propositional Logics (Propositional logic (PL) is the simplest form of logic where all
the statements are made by propositions. A proposition is a declarative statement
which is either true or false. It is a technique of knowledge representation in logical
and mathematical form.)
 Predicate logics (A predicate is an expression of one or more variables determined
on some specific domain. A predicate with variables can be made a proposition by
either authorizing a value to the variable or by quantifying the variable.)

Advantages of Logical Representation:

1. Logical representation enables us to do logical reasoning.

2. Logical representation is the basis for the programming languages.

Disadvantages of Logical Representation:

1. Logical representations have some restrictions and are challenging to work with.
2. Logical representation technique may not be very natural, and inference may not
be so efficient.

2. Semantic Network:
As the name suggests this type of representation works with a network of data. In the
network, the blocks define objects, and the edges (or arcs) define the relationships
between the blocks. Although semantic networks take more computational time, their use
is extensive as the knowledge represented is simple to understand. Semantic networks
are alternative of predicate logic for knowledge representation. In Semantic networks, we
can represent our knowledge in the form of graphical networks. This network consists of
nodes representing objects and arcs which describe the relationship between those
objects. Semantic networks can categorize the object in different forms and can also link
those objects. Semantic networks are easy to understand and can be easily extended.

Example: Following are some statements which we need to represent in the form of
nodes and arcs.

Statements:

a. Jerry is a cat.
b. Jerry is a mammal
c. Jerry is owned by Priya.
d. Jerry is brown colored.
e. All Mammals are animal.

In the above diagram, we have represented the different type of knowledge in the form
of nodes and arcs. Each object is connected with another object by some relation.

Advantages of Semantic Network:

1. Semantic networks are a natural representation of knowledge.

 2. Semantic networks convey meaning in a transparent manner.
3. These networks are simple and easily understandable.

Drawbacks in Semantic Network:

1. Semantic networks take more computational time at runtime as we need to

traverse the complete network tree to answer some questions. It might be possible
in the worst case scenario that after traversing the entire tree, we find that the
solution does not exist in this network.
2. Semantic networks do not have any standard definition for the link names.
3. These networks are not intelligent and depend on the creator of the system.

3. Frame Representation:

A frame is a collection of the attributes and the associated values. Frames are also
called slot-filler structures. This is because the slots are the attributes, and they are
filled by the values of those attributes which represent the knowledge in the
environment. Frames make the grouping of data and different object values easier.
But sometimes, the inference mechanism is challenging to implement or use as it is a
quite generalized approach.

Frames are derived from semantic networks and later evolved into our modern-day
classes and objects. A single frame is not much useful. Frames system consist of a
collection of frames, which are connected. In the frame, knowledge about an object or
event can be stored together in the knowledge base. The frame is a type of technology
which is widely used in various applications including Natural language processing
and machine visions.

Example:

Let's take an example of a frame for a book

Slots Filters

Title Artificial Intelligence

Genre Computer Science

Author Peter Norvig

 Edition Third Edition

Year 1996

Page 1152

Advantages of Frame Representation:

1. The frame knowledge representation makes the programming easier by grouping

the related data.
2. The frame representation is comparably flexible and used by many applications in
AI.
3. It is very easy to add slots for new attribute and relations.
4. It is easy to include default data and to search for missing values.
5. Frame representation is easy to understand and visualize.

Disadvantages of Frame Representation:

1. In frame system inference mechanism is not be easily processed.

2. Inference mechanism cannot be smoothly proceeded by frame representation.
3. Frame representation has a much generalized approach.

4. Production Rules:

Production rules system consist of (condition, action) pairs which mean, "If condition
then action". It has mainly three parts:

o The set of production rules

o Working Memory
o The recognize-act-cycle

In production rules agent checks for the condition and if the condition exists then
production rule fires and corresponding action is carried out. The condition part of the
rule determines which rule may be applied to a problem. And the action part carries out
the associated problem-solving steps. This complete process is called a recognize-act
cycle.
The working memory contains the description of the current state of problems-solving
and rule can write knowledge to the working memory. This knowledge match and may
fire other rules.

If there is a new situation (state) generates, then multiple production rules will be fired
together, this is called conflict set. In this situation, the agent needs to select a rule from
these sets, and it is called a conflict resolution.

Example:

o IF (at bus stop AND bus arrives) THEN action (get into the bus)
o IF (on the bus AND paid AND empty seat) THEN action (sit down).
o IF (on bus AND unpaid) THEN action (pay charges).
o IF (bus arrives at destination) THEN action (get down from the bus).

Advantages of Production Rule:

1. The production rules are expressed in natural language.

2. The production rules are highly modular, so we can easily remove, add or modify
an individual rule.

Disadvantages of Production Rule:

1. Production rule system does not exhibit any learning capabilities, as it does not
store the result of the problem for the future uses.
2. During the execution of the program, many rules may be active hence rule-based
production systems are inefficient.

Script:
A script is a structured representation describing a stereotyped sequence of events
in a particular context.
Scripts are used in natural language understanding systems to organize a knowledge
base in terms of the situations that the system should understand. Scripts use a
frame-like structure to represent the commonly occurring experience like going to
the movies eating in a restaurant, shopping in a supermarket, or visiting an
ophthalmologist.
 Thus, a script is a structure that prescribes a set of circumstances that could be
expected to follow on from one another.

Components of a script:
The components of a script include:
 Entry condition: These are basic condition which must be fulfilled before events
in the script can occur.
 Results: Condition that will be true after events in script occurred.
 Props: Slots representing objects involved in events
 Roles: These are the actions that the individual participants perform.
 Track: Variations on the script. Different tracks may share components of the
same scripts.
 Scenes: The sequence of events that occur.

Describing a script, special symbols of actions are used. These are:

Symbol Meaning Example

ATRANS transfer a relationship give
transfer physical location of an
PTRANS go
object
PROPEL apply physical force to an object push
MOVE move body part by owner kick
GRASP grab an object by an actor hold
INGEST taking an object by an animal eat drink
EXPEL expel from animal’s body cry
MTRANS transfer mental information tell
MBUILD mentally make new information decide
conceptualize or think about an
CONC think
idea
SPEAK produce sound say
ATTEND focus sense organ listen

Example:-Script for going to the bank to withdraw money.

SCRIPT : Withdraw money

TRACK : Bank
PROPS : Money
Counter
Form
Token
Roles : P= Customer
E= Employee
C= Cashier
Entry conditions: P has no or less money.
The bank is open.
Results : P has more money.
Scene 1: Entering
P PTRANS P into the Bank
P ATTEND eyes to E
P MOVE P to E
Scene 2: Filling form
P MTRANS signal to E
E ATRANS form to P
P PROPEL form for writing
P ATRANS form to P
E ATRANS form to P
Scene 3: Withdrawing money
P ATTEND eyes to counter
P PTRANS P to queue at the counter
P PTRANS token to C
C ATRANS money to P
Scene 4: Exiting the bank
P PTRANS P to out of bank
Advantages of Scripts:

 Ability to predict events.

 A single coherent interpretation maybe builds up from a collection of
observations.

Disadvantages of Scripts:

 Less general than frames.

 May not be suitable to represent all kinds of knowledge