Ai systems history

Question 1

What is Intelligence?

Answer 1

Intelligence is the ability to understand and learn new things.

Question 2

Did computers pass the turing test?

Answer 2

No

Question 3

What are the Big Data vs?

Answer 3

Volume, Velocity and Variety

Question 4

What the first AI Algorithm?

Answer 4

Neural Network

Question 5

Why it was the first Algorithm?

Answer 5

To simulate the human brain

Question 6

What is GPS?

Answer 6

General Problem Solver, was the most ambitious project in the area of great expectations, aiming for a program that can solve problems using human brain methods.

Question 7

Did GPS Succeed?

Answer 7

No

Question 8

What are Expert Systems?

Answer 8

Systems designed to solve typical cases in narrow areas of expertise.

Question 9

Name four expert systems

Answer 9

MYCIN,PROSPECTOR,EMYCIN and DENDRAL

Question 10

What is the weakness of expert systems?

Answer 10

They are so strict to there knowledge base, they can not relate accumulated , heuristic knowledge to any deeper
understanding of the problem domain.
They take a long time to build.
They can’t recognize their domain boundaries, if they faced a task different than typical problems they might try to solve it and fail.

Question 11

What is fuzzy logic?

Answer 11

Logic that is multi-valued. It deals with
degrees of membership and degrees of truth.

Question 12

What are Fuzzy sets?

Answer 12

A fuzzy set can be simply defined as a set with fuzzy boundaries.

Question 13

What is a fuzzy rule?

Answer 13

A fuzzy rule can be defined as a conditional statement in the form.

Question 14

What are fuzzy experts systems variables?

Answer 14

Linguistic Variables.

Question 15

What are the advantages of fuzzy experts systems?

Answer 15

Improved computational power, Improved cognitive modelling and The ability to represent multiple experts.

Question 16

What is the disadvantage of a fuzzy expert systems?

Answer 16

The rules must be highly tuned and tested.

Question 17

What is knowledge?

Answer 17

a theoretical or practical
understanding of a subject or a domain.

Question 18

What are experts?

Answer 18

Those who possess knowledge are called experts

Question 19

What is a domain expert?

Answer 19

domain expert if he or
she has deep knowledge (of both facts and rules)
and strong practical experience in a particular
domain.

Question 20

What is a rule?

Answer 20

an IF-THEN structure that relates given
information or facts in the IF part to some action in
the THEN part.

Question 21

What is the IF part called?

Answer 21

antecedent (premise or condition)

Question 22

What is the THEN part called?

Answer 22

consequent (conclusion or
action)

Question 23

Can a rule have multiple antecedents?

Answer 23

Yes

Question 24

What are the components of an antecedent?

Answer 24

Linguistic Object and its value, they are both linked by an operator.

Question 24

What are operators like is, are, is not and are not used for?

Answer 24

To assign a symbolic value to a linguistic object.

Question 24

What else can expert define?

Answer 24

Numerical objects, and assign numerical values to it using mathematical operators.

Question 25

What can rules represent?

Answer 25

Relations, recommendations , directives , strategies and heuristics.

Question 26

What are the five members of the expert system development team?

Answer 26

The domain expert, The knowledge engineer, the programmer , the project manager and the user.

Question 27

The success of their expert system entirely depends on how well the members work together.

Answer 27

True.

Question 28

What is the domain expert role?

Answer 28

is a knowledgeable and skilled
person capable of solving problems in a specific area or domain. This person has the greatest expertise in a given domain. This expertise is to be expertise in a given domain. This expertise is to be
captured in the expert system. Therefore, the expert must be able to communicate his or her knowledge, be willing to participate in the expert system development and commit a substantial amount of time to the project. The domain expert is the most important player in the expert system
development team

Question 29

What is the knowledge engineer role?

Answer 29

The knowledge engineer is someone who is capable of designing, building and testing an expert system.
of designing, building and testing an expert system.
He or she interviews the domain expert to find out how a particular problem is solved. The knowledge engineer establishes what reasoning methods the
expert uses to handle facts and rules and decides how to represent them in the expert system. The knowledge engineer then chooses some development software or an expert system shell, or looks at programming languages for encoding the
knowledge. And finally, the knowledge engineer is responsible for testing, revising and integrating the expert system into the workplace

Question 30

What is the programmer role?

Answer 30

The programmer is the person responsible for the
actual programming, describing the domain
knowledge in terms that a computer can
understand. The programmer needs to have skills
in symbolic programming in such AI languages as
LISP, Prolog and OPS5 and also some experience
in the application of different types of expert
system shells. In addition, the programmer should
know conventional programming languages like C,
Pascal, FORTRAN and Basic.

Question 31

What is the project manager?

Answer 31

The project manager is the leader of the expert
system development team, responsible for keeping
the project on track. He or she makes sure that all
the project on track. He or she makes sure that all
deliverables and milestones are met, interacts with
deliverables and milestones are met, interacts with
the expert, knowledge engineer, programmer and
end-user.

Question 32

Is designing the UI essential? Why?

Answer 32

Yes, The user must not only be confident in the expert
system performance but also feel comfortable using
it.

Question 33

What is the production model based on?

Answer 33

the idea that
humans solve problems by applying their knowledge
(expressed as production rules) to a given problem
represented by problem-specific information.