EXCEL ENGINEERING COLLEGE
(Autonomous)
B.Tech – Information Technology
IV SEMESTER
20IT402 COMPUTATIONAL INTELLIGENCE
Regulations 2020
Question Bank with Answers
UNIT – I INTRODUCTION
PART- A
Q.No Questions Marks CO BL
What is first-order logic?
1 • The first-order logic is sufficiently expressive to represent a good deal of 2 CO2 R
our commonsense knowledge.
• It also either subsumes or forms the foundation of many other
representation languages
What is a symbol? 2
2 CO2 U
• The basic syntactic elements of first-order logic are the symbols.
• It stands for objects, relations and functions
What are the types of Quantifiers?
2
3 The types of Quantifiers are, CO2 U
1.Universal Quantifiers
2. Existential Quantifiers
What are the three kinds of symbols?
The three kinds of symbols are, 2
4 CO2 R
Constant symbols standing for objects;
Predicate symbols standing for relations;
Function symbols standing for functions.
Define a Proof.
• A sequence of application of inference rules is called a proof. 2
5 Finding proof is exactly finding solution to search problems. CO2 U
• If the successor function is defined to generate all possible applications of
inference rules then the search algorithms can be applied to find proofs.
What are the basic Components of propositional logic?
The basic Components of propositional logic
Logical Constants (True, False) 2
6 CO3 R
Propositional symbols (P, Q)
Logical Connectives (^,=, , )
, What is forward chaining?
• A deduction to reach a conclusion from a set of antecedents is
called forward chaining. 2
7 CO3 U
• In other words, the system starts from a set of facts, and a set of
rules, and tries to find the way of using these rules and facts
to deduce a conclusion or come up with a suitable course of
action.
What is backward chaining?
2
8 In backward chaining, we start from a conclusion, which is the hypothesis we CO3 R
wish to prove, and we aim to show how that conclusion can be reached from
the rules and facts in the data base.
Define Modus Ponen’s rule in Propositional logic?
The standard patterns of inference that can be 2
9 CO3 U
applied to derive chains of conclusions that
lead to the desired goal is said to be Modus
Ponen’s rule.
Define a sentence.
• Each individual representation of
fact is called a sentence.
2
10 • The sentences are expressed in a CO3 R
language called as knowledge
representation language.
What is CRISP set?
2
11 If characteristic function µA(x) has only values 0 ('false') and 1 CO3 U
('true''). Such sets are crisp sets.
Sketch fuzzy rules.
• Fuzzy rule is a conditional statement. 2
12 CO3 R
• The form of fuzzy rules is given by IF THEN statements
What are the characteristics of fuzzy inference system?
• The output from FIS is always a fuzzy set irrespective of its input
which can be fuzzy or crisp. 2
13 CO2 U
• It is necessary to have fuzzy output when it is used as a controller.
• A defuzzification unit would be there with FIS to convert fuzzy
variables into crisp variables.
What is the difference between traditional logic and temporal logic?
2
14 Temporal logic is a formal system for specifying and reasoning about CO2 U
concurrent programs.
What is a membership function? 2
15 CO2 R
A membership function (MF) is a curve that defines how each
, point in the input space is mapped to a membership value (or degree of
membership) between 0 and 1
What is fuzzy set?
2
16 Fuzzy set theory permits membership function valued in the CO2 R
interval [0,1]. Example: Words like young, tall, good or high are fuzzy.
What are the advantages and disadvantages of fuzzy logic?
Advantages
• cheaper to develop
• cover a wider range of operating conditions
17
• more readily customizable in natural language terms. 2
CO2 A
Dis Advantages
• A fuzzy logic controller totally depends on human knowledge and
expertise.
• These controllers cannot recognize machine learning or neural
networks.
Give examples for fuzzy system. 2
18 CO3 R
Example: Words like young, tall, good or high are fuzzy.
What is ANN?
• Artificial neural network (ANN) is a computational model that 2
19 CO2 R
consists of several processing elements that receive inputs and
deliver outputs based on their predefined activation functions.
What is the need for probability theory in uncertainty?
• Probability provides the way of summarizing the uncertainty that comes
2
20 from our laziness and ignorance. CO2 U
• Probability statements do not have quite the same kind of semantics
known as evidences.
PART- B
Q.No Questions Marks CO BL
Explain Fuzzy Room Cooler System.
The conventional room cooler implemented using a fan encased in a box
with wool or hay that is continously moistened by a trickle of water.
A motorized pump controls the rate of flow of water required for
moistening.Two sensors mounted inside the cooler, measure the fan motor
speed and the temperature within the room. The fan speed could be varied
1 CO2 U
either by a knob or by a user. The basic aim here is to achieve a smooth
control and also save on water, a precious resource.
We need to maintain the temperature of the room.only the rate of
flow of water needs to be controlled based on the speed of the fan and the
temperature.
Fuzzy Regions:
(Autonomous)
B.Tech – Information Technology
IV SEMESTER
20IT402 COMPUTATIONAL INTELLIGENCE
Regulations 2020
Question Bank with Answers
UNIT – I INTRODUCTION
PART- A
Q.No Questions Marks CO BL
What is first-order logic?
1 • The first-order logic is sufficiently expressive to represent a good deal of 2 CO2 R
our commonsense knowledge.
• It also either subsumes or forms the foundation of many other
representation languages
What is a symbol? 2
2 CO2 U
• The basic syntactic elements of first-order logic are the symbols.
• It stands for objects, relations and functions
What are the types of Quantifiers?
2
3 The types of Quantifiers are, CO2 U
1.Universal Quantifiers
2. Existential Quantifiers
What are the three kinds of symbols?
The three kinds of symbols are, 2
4 CO2 R
Constant symbols standing for objects;
Predicate symbols standing for relations;
Function symbols standing for functions.
Define a Proof.
• A sequence of application of inference rules is called a proof. 2
5 Finding proof is exactly finding solution to search problems. CO2 U
• If the successor function is defined to generate all possible applications of
inference rules then the search algorithms can be applied to find proofs.
What are the basic Components of propositional logic?
The basic Components of propositional logic
Logical Constants (True, False) 2
6 CO3 R
Propositional symbols (P, Q)
Logical Connectives (^,=, , )
, What is forward chaining?
• A deduction to reach a conclusion from a set of antecedents is
called forward chaining. 2
7 CO3 U
• In other words, the system starts from a set of facts, and a set of
rules, and tries to find the way of using these rules and facts
to deduce a conclusion or come up with a suitable course of
action.
What is backward chaining?
2
8 In backward chaining, we start from a conclusion, which is the hypothesis we CO3 R
wish to prove, and we aim to show how that conclusion can be reached from
the rules and facts in the data base.
Define Modus Ponen’s rule in Propositional logic?
The standard patterns of inference that can be 2
9 CO3 U
applied to derive chains of conclusions that
lead to the desired goal is said to be Modus
Ponen’s rule.
Define a sentence.
• Each individual representation of
fact is called a sentence.
2
10 • The sentences are expressed in a CO3 R
language called as knowledge
representation language.
What is CRISP set?
2
11 If characteristic function µA(x) has only values 0 ('false') and 1 CO3 U
('true''). Such sets are crisp sets.
Sketch fuzzy rules.
• Fuzzy rule is a conditional statement. 2
12 CO3 R
• The form of fuzzy rules is given by IF THEN statements
What are the characteristics of fuzzy inference system?
• The output from FIS is always a fuzzy set irrespective of its input
which can be fuzzy or crisp. 2
13 CO2 U
• It is necessary to have fuzzy output when it is used as a controller.
• A defuzzification unit would be there with FIS to convert fuzzy
variables into crisp variables.
What is the difference between traditional logic and temporal logic?
2
14 Temporal logic is a formal system for specifying and reasoning about CO2 U
concurrent programs.
What is a membership function? 2
15 CO2 R
A membership function (MF) is a curve that defines how each
, point in the input space is mapped to a membership value (or degree of
membership) between 0 and 1
What is fuzzy set?
2
16 Fuzzy set theory permits membership function valued in the CO2 R
interval [0,1]. Example: Words like young, tall, good or high are fuzzy.
What are the advantages and disadvantages of fuzzy logic?
Advantages
• cheaper to develop
• cover a wider range of operating conditions
17
• more readily customizable in natural language terms. 2
CO2 A
Dis Advantages
• A fuzzy logic controller totally depends on human knowledge and
expertise.
• These controllers cannot recognize machine learning or neural
networks.
Give examples for fuzzy system. 2
18 CO3 R
Example: Words like young, tall, good or high are fuzzy.
What is ANN?
• Artificial neural network (ANN) is a computational model that 2
19 CO2 R
consists of several processing elements that receive inputs and
deliver outputs based on their predefined activation functions.
What is the need for probability theory in uncertainty?
• Probability provides the way of summarizing the uncertainty that comes
2
20 from our laziness and ignorance. CO2 U
• Probability statements do not have quite the same kind of semantics
known as evidences.
PART- B
Q.No Questions Marks CO BL
Explain Fuzzy Room Cooler System.
The conventional room cooler implemented using a fan encased in a box
with wool or hay that is continously moistened by a trickle of water.
A motorized pump controls the rate of flow of water required for
moistening.Two sensors mounted inside the cooler, measure the fan motor
speed and the temperature within the room. The fan speed could be varied
1 CO2 U
either by a knob or by a user. The basic aim here is to achieve a smooth
control and also save on water, a precious resource.
We need to maintain the temperature of the room.only the rate of
flow of water needs to be controlled based on the speed of the fan and the
temperature.
Fuzzy Regions:
