Artificial Intelligence

Contents

Knowledge Representation Rule-Based Representation Frame-Based Representation Semantic-Networks

2

What is frame? A frame is a data structure with typical knowledge about a

particular object or concept. Followings are two typical frames with knowledge about airline

passengers. Both frames have the same structure. Each frame has its own name & a set of attributes or slots,

associated with it.

QUANTAS BOARDING PASSCarrier: QUANTAS AIRWAYSName: MR N BLACKFlight: QF 612Data: 29DECSeat: 23AFrom: HOBARTTO: MELBOURNEBoarding:0620Gate: 2

AIR NEW ZEALAND BOARDING PASSCarrier: AIR NEW ZEALANDName: MRS J WHITEFlight: NZ 0198Data: 23NOVSeat: 27KFrom: MELBOURNETO: CHRISTCHURCHBoarding:1815Gate: 4

Frames as knowledge representation technique

The concept of a frame is defined by a collection of slots or attributes.

Each slot describes a particular attribute or operation of the frame.

Slots are used to store values.A slot may contain a default value or a pointer to another

frame, a set of rules or procedure by which the slot value is obtained.

There are 3 types of relationships between objects:Generalization:

It denotes “a-kind-of” or “is-a” relationship

between super-class and its sub-class.

For example, a car is-a vehicle, or in other words,

Car represents a subclass of the more general

super-class Vehicle.

How are objects related in a frame-based system?

CLASS: Vehicle

CLASS: Boat CLASS: Car CLASS: Airplane

is-a is-a is-a

Superclass: Vehicle Superclass: Vehicle Superclass: Vehicle

Generalization

Aggregation:

It is “a-part-of” or “part-whole” relationship in which

several subclass representing components are

associated with a super-class representing

components are associated with a super-class

representing a whole.

For example, an engine is a part of a car.

How are objects related in a frame-based system?

CLASS: Car

CLASS:Chassis CLASS:Engine CLASS:Transmission

a-part-of

Superclass: Car Superclass:Car Superclass:Car

Aggregation

a-part-of a-part-of

Association

It describes some relationship between

different classes which are unrelated otherwise.

For example, Mr. Black owns a car.

How are objects related in a frame-based system?

CLASS: Mr. Black

CLASS:House CLASS: Car CLASS: Computer

Superclass: Mr. Black Superclass: Mr. Black Superclass:Mr. Black

Association

Belongs-toBelongs-to

Belongs-to

ownsowns owns

Frame-Based Knowledge Representation

We can define the given problem in abstract way.

Frames provide a way for the structured and concise

representation of knowledge.

In a single entity, a frame combines all necessary

knowledge about a particular object or concept.

During a search for a specific item, we go directly to the

item’s instance frame that contains the desired goal.

Frame-Based Knowledge RepresentationAdvantages

Idea behind the frame based system is easy, but

implementation is difficult.

It can not distinguish between essential properties and

accidental properties of a frame.

Hence, in a complex case, it is difficult to predict how these

features will interact, or to explain unexpected interactions,

which makes debugging and updating difficult.

Frame-Based Knowledge RepresentationDisadvantages

Semantic NetworkSN was first proposed by Quillian in 1966, as a model of human

memory

Semantic network (SN) is a graph-based representation

It is a directed graph

A SN is a network of nodes and links to represent the definition

of a concept (or a collection of concepts)

The nodes represent concepts

The links represent the relations between concepts

Semantic NetworkIn these networks, objects are shown by nodes, and links

between the nodes describe

the relationship between two objects, for example,Mary is an instance of trainer and trainer is a type of consultant. A trainer trains a programmer and a programmer is an employee.Joe is an instance of programmer.

From this we can clearly see the relationship that may exist

between Mary and Joe.

ExampleDraw a diagram representing the relationships between Mary and Joe, indicating the relationship between a trainer, consultant, programmer and employee.

ExampleSuch a diagram is the beginning of a semantic network but this can be improved by more closely defining the nature of the relationships.

Inheritance

Inheritance is concerned with how one object inherits the properties

of another object.

In the diagram you created in the previous activities, identify from

which classes Mary and Joe inherit properties.

You should have been able to recognize that Mary, in being a trainer,

inherits the properties of the consultant class and that Joe, in being a

programmer, inherits the properties of the employee class.

Inheritance

Inheritance

You should have been able to recognize that from this semantic network it

would be possible to conclude that the grass snake Slither is a vegetarian

and Slither eats meat. Clearly, these conclusions are contradictory. Which

conclusion we reach depends where in the network we start and which links

we follow. This process is unreliable.

Thus, to perform inference using a semantic network you must understand

the meaning of the links and follow the correct links. As the links can be

many, and varied, performing inference using a semantic network is

complex and unreliable.

Vertebrata Cat Fur

Animal Mammal Bear

FishWater

Whale

is-an is-a

is-anis-a

Lives-in

Is-a

has

has

Has-a is-a

ExampleMammal is a kind of animal that has vertebrata. Cat, Bear and whale are mammal. Cat and Bear has fur. Fish is a type of animal. Whale is a Fish and Fish lives in water.

Advantages

Explicit in visualization and easy to understand

Often used as a communication tool between the knowledge engineer

and the expert during the knowledge acquisition phase

SNs are particularly good at representing knowledge in the form of

hierarchies

Knowledge is hierarchically categorized (classified)

Quick inference possible

Supports default reasoning in finite time

Disadvantages

No interpretation standard – Lack well-defined semantics

They are less reliable than other knowledge representation

techniques because inferring becomes a process of searching

across the diagram.

Quite limited inference possible

Diagrams can become very complex.

THANK YOU