Slide 1 : Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi ARTIFICIAL INTELLIGENCE (AI) -
KNOWLEDGE REPRESENTATION SCHEMES
Ruchi Sharma
ruchisharma1701@gmail.com
Slide 2 : Contents Quick Recall – AI concept
Knowledge Representation – Concept & Features
Knowledge Representation - Techniques/Schemes
Understanding Semantic Networks – Facts
Understanding Semantic Networks – Examples
Understanding Frames – Facts
Understanding Frames – Examples
Understanding Propositional Logic & FOPL – Facts
Understanding Propositional Logic & FOPL - Examples
Understanding Rule-based Systems - Facts
Understanding Rule-based Systems - Examples Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 3 : Quick Recall – AI Concepts Artificial Intelligence deals with creating computer systems that can
simulate human intelligent behaviour in a particular domain
learn new concepts and tasks
reason & draw conclusions
learn from the examples & past related experience
A computer possessing artificial intelligence( an expert system) has two basic parts
Knowledge Base – containing the knowledge it uses
Inference-control unit – which facilitates the appropriate & contextual use of KB Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 4 : Knowledge Representation – Concept & Features Knowledge representation is a method used to code knowledge in the knowledge base of an expert system.
An ideal knowledge representation scheme should
have inferencing capability
have a set of well defined syntax & semantics
allow the knowledge engineer to express knowledge in a language ( which can be inferred)
allow new knowledge to be inferred from the basic facts already stored in the KB Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 5 : Knowledge Representation – Techniques/Schemes Different knowledge representation schemes are used today among which the most common are
Semantic Networks
Frames
Propositional logic & FOPL
Rule-based system Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 6 : A semantic network is a directed graph with labelled nodes & arrows. Nodes are commonly used for objects & the arrows for relations.
The pictorial representation of objects, their attributes & relationships between them & other entities make them better than many other representation schemes. Understanding Semantic Networks - Facts Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 7 : Let us make a semantic net with the following piece of information
“Tweety is a yellow bird having wings to fly.”
Fact 1 : Tweety is a bird.
Fact 2 : Birds can fly.
Fact 3 : Tweety is yellow in color. Understanding Semantic Networks – An example Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 8 : Frames are record-like structures that have slots & slot-values for an entity
Using frames, the knowledge about an object/event can be stored together in the KB as a unit
A slot in a frame
specify a characteristic of the entity which the frame represents
Contains information as attribute-value pairs, default values etc. Understanding Frames – Facts Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 9 : Understanding Frames - Examples An example frame corresponding to the semantic net eg quoted earlier
(Tweety
(SPECIES (VALUE bird))
(COLOR (VALUE yellow))
(ACTIVITY (VALUE fly)))
Employee Details
( Ruchi Sharma
(PROFESSION (VALUE Tutor))
(EMPID (VALUE 376074))
(SUBJECT (VALUE Computers))) Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 10 : Understanding Propositional Logic – Facts Symbolic logic is a formalized system of logic which employs abstract symbols of various aspects of natural language.
Propositional logic is the simplest form of the symbolic logic, in which the knowledge is represented in the form of declarative statements called propositions.
Each proposition, denoted by a symbol, can assume either of the two values – true or false.
Eg
P : It is raining.
Q : The visibility is low. Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 11 : Understanding Propositional Logic – Facts (Contd.) Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 12 : Understanding Propositional Logic - Examples Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 13 : Understanding First order predicate logic (FOPL) FOPL was developed to extend the expressiveness of propositional logic.
It works by breaking a proposition into various parts & representing them as symbols.
The symbolic structure includes
individual symbols - some constants as names
variable symbols – as x, y, a, b etc
function symbols – as ‘product’
predicate symbols – as P, Q etc Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 14 : Understanding FOPL - Example Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 15 : Understanding Rule-based System – Facts A Rule-based system represents knowledge in the form of a set of rules .
Each rule represents a small chunk of knowledge relating to the given domain.
A number of related rules along with some known facts collectively may correspond to a chain of inferences.
An interpreter(inference engine) uses the facts & rules to derive conclusions about the current context & situation as presented by the user input. Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 16 : Understanding Rule-based System – Example Suppose a rule-based system has the following statements
R1 : If A is an animal and A lays no eggs, then A is a mammal.
F1 : Lucida is an animal.
F2 : Lucida lays no eggs.
The inference engine will update the rule base after interpreting the above set as :
R1 : If A is an animal and A lays no eggs, then A is a mammal.
F1 : Lucida is an animal.
F2 : Lucida lays no eggs.
F3 : Lucida is a mammal. Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi
Slide 17 : Thank You Ruchi Sharma ruchisharma1701@gmail.com http://www.wiziq.com/tutor-profile/376074-Ruchi