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Frames are knowledge representation techniques frequently used in AI, knowledge engineering. The concept is similar to inheritance in an OOP paradigm.
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FRAMES
By:
Abisekh Bahadur Niraula (071/MSCSKE/651)
Rasu Shrestha (071/MSCSKE/662)
Shikhar Basnet (071/MSCSKE/666)
Umesh Timalsina (071/MSCSKE/669)
Department of Electronics and Computer Engineering
IOE, Pulchowk Campus
1. FRAMES- INTRODUCTION:o Knowledge Representation Technique
o Similar to Semantic Nets.
o Proposed by: Marvin Minsky in 1974.
o Article: A Framework For Representing Knowledge.
o Common Sense System: Not Rule Based.
o AIs Primary Data Structures.
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1. FRAMES- INTRODUCTION-II:o Frame: Prototype of a Concept
o Denoting attributes of the concept
o The class of objects or concepts to which the concept inquestion belongs.
o And some other things
o An instance of a Frame.
o Representation of a specific object.
o Semantic Nets with Attributes.
o Description: Similar to Structure Data Type in C.
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1. FRAMES- INTRODUCTION-III:o A frame represents an entity as a set of slots
(attributes) and associated values
o Represents:
o General Concept (Frame)
o Specific Entry (Instance of the Frame)
o Implicit Relation with other Frames.
o Concept: Similar to OOS(Object Oriented Systems)
o Hierarchical Representations: Super and Sub Classes.
o Classes and Frames: Used interchangebly.
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2. EXAMPLES: 5
2. EXAMPLES-HIERARCHY: 6
2. EXAMPLES-HIERARCHY: 7
2. EXAMPLES- I:o FIDO is a Dog.
o Dog is a concept.
o Fido is a Particular dog.
How Can We Represent the Concept/ Notion of theCreature Dog?
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2. EXAMPLES:o FIDO is a Dog.
o Dog is a concept.
o Fido is a Particular dog.
How Can We Represent the Concept/ Notion of theCreature Dog?
A Way: ANIMALS>>>MAMMALS>>DOG
o FIDO: an instance of the Frame Dog.
o Notion of Frames: Felt by people out of CommonSense.
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2. EXAMPLES- FRAME: 10
SLOT NAME SLOT VALUES(Default)
IS_A Mammal
No_of_legs 4
Has_Tail Yes
Color_of_Skin
Owner
Type_of_Teeth Sharp
DOG:
2. EXAMPLES- FRAME: 11
SLOT NAME SLOT VALUES
IS A Mammal
No_of_legs 4
Has Tail Yes
Color of Skin White
Owner Shikhar
Type of Teeth Sharp
FIDO:
2. EXAMPLES- FRAME: 12A Book Frame:
Book Frame
Slot Filler
Title AI. A modern Approach
Author Russell & Norvig
Year 2003
2. EXAMPLES- FRAME: 13Inheritance: Similar to OOP Paradigm.
Hotel Room
what room
where hotel
contains
hotel chair
hotel phone
hotel bed
Hotel Chair
what chair
height 20-40cm
legs 4Hotel Phone
what phone
billing guest
Hotel Bed
what bed
size king
part mattressMattress
price 100$
3. SLOTS:o Slots Denote Attributes.
o Attributes are typed.
o Some Values: Already Instantiated.
o Some Values: Defined in the Instances only.
o Instantiated Slots: May be Used to AnswerQueries.
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3. SLOTS-II:Slots Can Contain:
o Values
o Types
o Constraints Over Possible Values
o Predicates:
o Daemons/ Functions.
o Slots Can be Structured- Frames Within the Slots-Frame Pointers.
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3. SLOTS-III:o Constraints over Possible Values:
BOY:
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Is_a Human_being Type Constraints
Name String
Age Float
3. SLOTS-IV:Predicates in a slot:
o Two Types of Predicates in General:
o If needed
o If added.
o If needed: State How to Find a Value.
o If added: Used to check constraints on the Values.
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3. SLOTS-IV:o Predicates in a slot- Example:
BOY:
If needed compute CGPA(BOY, results)
If added test(constraint).
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Is_a Human_being Type
Name String
Age Float
4. INHERITENCE: 19Question: Does Tom drink Milk?
TOM is an instance of BOY.
Also, Boy is a HUMAN BEING.
HUMAN BEINGS drink milk.
All Human Beings Drink Milk.
The answer can be inherited.
5. GENERIC and DEFAULT VALUES:o Generic Values:
o Hold True for all instances and sub-classes of the class.
o Inherited Down the Hierarchy
o Default Values:
o Filler Values
o Default Values may be over-written.
o Specified in the Parent-Class(Super Class).
o Conflicts: Multiple Inheritance.
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6. INFERENCE IN A FRAME:o Look for Candidate Frame or Instances.
o Look for Availability of Values.
o If Available- Solved.
o Else go to Preceding Level and so on.
o If Solved at a Higher Level, try to have MoreSpecific Answers Going Down the hierarchy.
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7. ANSWERING QUERIES- EXAMPLE: 22
9. ADVANTAGES: 23o Makes programming easier by grouping related
knowledge
o Easily understood by non-developers
o Expressive power
o Easy to set up slots for new properties and relations
o Easy to include default information and detect missing values.
9. DISADVANTAGES: 24o No standards (slot-filler values)
o More of a general methodology than a specific representation:o Frame for a class-room will be different for a professor and
for a maintenance worker
o No associated reasoning/inference mechanisms
10. REFERENCES: 251. Artificial Intelligence, Lecture-20, Prof. Dr.
Anupam Basu, Department of Computer Scienceand Engineering, IIT Kharagpur, NPTEL, MHRD,Government of India
11. QUERIES?? 26
THANK-YOU