Define Boundary set.

Define Boundary set.
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Answer :

 Each boundary will not be a point but rather a set of hypotheses called a Boundary set. 
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The region of universe that is characterized by complete membership in the set is called A. Core B. Support C. Boundary D. Fuzzy

Description : The region of universe that is characterized by complete membership in the set is called A. Core B. Support C. Boundary D. Fuzzy

Last Answer : A. Core

Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median

Description : Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median

Last Answer : C. Core, Support , Boundary

What are the two boundary sets?

Description : What are the two boundary sets?

Last Answer : i. G Set : a most general boundary set.  ii. S Set : a most specific boundary set.

Define magic set.

Description : Define magic set. 

Last Answer : To rewrite the rule set, using information from the goal, so that only relevant variable bindings called magic set.

Define Cycle cut set.

Description : Define Cycle cut set.

Last Answer : The process of choosing a subset S from variables [CSP] such that the constraint graph becomes a tree after removal of S. S is called a cycle cut set. 

In LISP, what is the function assigns the symbol x to y? a) (setq y x) b) (set y = ‘x’) c) (setq y = ‘x’) d) (setq y ‘x’)

Description : In LISP, what is the function assigns the symbol x to y? a) (setq y x) b) (set y = ‘x’) c) (setq y = ‘x’) d) (setq y ‘x’)

Last Answer : d) (setq y ‘x’)

What is Weak AI? a) the embodiment of human intellectual capabilities within a computer b) a set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans c) the study of mental faculties using mental models implemented on a computer d) all of the mentioned

Description : What is Weak AI? a) the embodiment of human intellectual capabilities within a computer b) a set of computer programs that produce output that would be considered to reflect intelligence if it ... the study of mental faculties using mental models implemented on a computer d) all of the mentioned

Last Answer : c) the study of mental faculties using mental models implemented on a computer

____________ is measured by the number of mental structures we use, how abstract they are, and how elaborate they interact to shape our perceptions. a) intrapersonal structure b) perceptual set c) self-justification d) none of the mentioned

Description : ____________ is measured by the number of mental structures we use, how abstract they are, and how elaborate they interact to shape our perceptions. a) intrapersonal structure b) perceptual set c) self-justification d) none of the mentioned

Last Answer : d) none of the mentioned

What is a finite set of rules that specifies a language? a) Signs b) Communication c) Grammar d) Phrase

Description : What is a finite set of rules that specifies a language? a) Signs b) Communication c) Grammar d) Phrase

Last Answer : c) Grammar

What is defined by a set of strings? a) Signs b) Formal language c) Communication

Description : What is defined by a set of strings? a) Signs b) Formal language c) Communication

Last Answer : b) Formal language

Which cannot be represented by a set of attributes? a) Program b) Three-dimensional configuration of a protein molecule c) Agents

Description : Which cannot be represented by a set of attributes? a) Program b) Three-dimensional configuration of a protein molecule c) Agents

Last Answer : b) Three-dimensional configuration of a protein molecule

Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Description : Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Last Answer : d) All of the mentioned

What takes input as an object described by a set of attributes? a) Tree b) Graph c) Decision graph d) Decision tree

Description : What takes input as an object described by a set of attributes? a) Tree b) Graph c) Decision graph d) Decision tree

Last Answer : d) Decision tree

____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Description : ____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Last Answer : c) Fuzzy Set

There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. a) Hedges b) Lingual Variable c) Fuzz Variable d) None of the mentioned

Description : There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. a) Hedges b) Lingual Variable c) Fuzz Variable d) None of the mentioned

Last Answer : a) Hedges

Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND b) OR c) NOT d) All of the mentioned

Description : Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND b) OR c) NOT d) All of the mentioned

Last Answer : d) All of the mentioned

The values of the set membership is represented by ___________ a) Discrete Set b) Degree of truth c) Probabilities d) Both Degree of truth & Probabilities

Description : The values of the set membership is represented by ___________ a) Discrete Set b) Degree of truth c) Probabilities d) Both Degree of truth & Probabilities

Last Answer : b) Degree of truth

The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______ a) Fuzzy Set b) Crisp Set c) Fuzzy & Crisp Set d) None of the mentioned

Description : The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______ a) Fuzzy Set b) Crisp Set c) Fuzzy & Crisp Set d) None of the mentioned

Last Answer : a) Fuzzy Set

Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth. a) True b) False

Description : Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth. a) True b) False

Last Answer : a) True

The truth values of traditional set theory is ____________ and that of fuzzy set is __________ a) Either 0 or 1, between 0 & 1 b) Between 0 & 1, either 0 or 1 c) Between 0 & 1, between 0 & 1 d) Either 0 or 1, either 0 or 1

Description : The truth values of traditional set theory is ____________ and that of fuzzy set is __________ a) Either 0 or 1, between 0 & 1 b) Between 0 & 1, either 0 or 1 c) Between 0 & 1, between 0 & 1 d) Either 0 or 1, either 0 or 1

Last Answer : a) Either 0 or 1, between 0 & 1

Traditional set theory is also known as Crisp Set theory. a) True b) False

Description : Traditional set theory is also known as Crisp Set theory. a) True b) False

Last Answer : a) True

What is the form of Fuzzy logic? a) Two-valued logic b) Crisp set logic c) Many-valued logic d) Binary set logic

Description : What is the form of Fuzzy logic? a) Two-valued logic b) Crisp set logic c) Many-valued logic d) Binary set logic

Last Answer : c) Many-valued logic

In partial order plan. A. Relationships between the actions of the behavior are set prior to the actions B. Relationships between the actions of the behavior are not set until absolutely necessary Choose the correct option. a) A is true b) B is true c) Either A or B can be true depending upon situation d) Neither A nor B is true

Description : In partial order plan. A. Relationships between the actions of the behavior are set prior to the actions B. Relationships between the actions of the behavior are not set until absolutely necessary Choose the ... ) Either A or B can be true depending upon situation d) Neither A nor B is true

Last Answer : a) A is true

A semantic network is used when one has knowledge that is best understood as a set of concepts that are related to one another. a) True b) False

Description : A semantic network is used when one has knowledge that is best understood as a set of concepts that are related to one another. a) True b) False

Last Answer : a) True

A) Knowledge base (KB) is consists of set of statements. B) Inference is deriving a new sentence from the KB. Choose the correct option. a) A is true, B is true b) A is false, B is false c) A is true, B is false d) A is false, B is true

Description : A) Knowledge base (KB) is consists of set of statements. B) Inference is deriving a new sentence from the KB. Choose the correct option. a) A is true, B is true b) A is false, B is false c) A is true, B is false d) A is false, B is true

Last Answer : a) A is true, B is true

____________ is/are useful when the original formulation of a problem is altered in some way, typically because the set of constraints to consider evolves because of the environment. a) Static CSPs b) Dynamic CSPs c) Flexible CSPs d) None of the mentioned

Description : ____________ is/are useful when the original formulation of a problem is altered in some way, typically because the set of constraints to consider evolves because of the environment. a) Static CSPs b) Dynamic CSPs c) Flexible CSPs d) None of the mentioned

Last Answer : b) Dynamic CSPs

The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is called chronological-backtracking. It is also possible to go all the way to set of variable that caused failure. a) True b) False

Description : The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is ... also possible to go all the way to set of variable that caused failure. a) True b) False

Last Answer : a) True

_______________ are mathematical problems defined as a set of objects whose state must satisfy a number of constraints or limitations. a) Constraints Satisfaction Problems b) Uninformed Search Problems c) Local Search Problems d) All of the mentioned

Description : _______________ are mathematical problems defined as a set of objects whose state must satisfy a number of constraints or limitations. a) Constraints Satisfaction Problems b) Uninformed Search Problems c) Local Search Problems d) All of the mentioned

Last Answer : a) Constraints Satisfaction Problems

A production rule consists of ____________ a) A set of Rule b) A sequence of steps c) Set of Rule & sequence of steps d) Arbitrary representation to problem

Description : A production rule consists of ____________ a) A set of Rule b) A sequence of steps c) Set of Rule & sequence of steps d) Arbitrary representation to problem

Last Answer : c) Set of Rule & sequence of steps

The Set of actions for a problem in a state space is formulated by a ___________ a) Intermediate states b) Initial state c) Successor function, which takes current action and returns next immediate state d) None of the mentioned

Description : The Set of actions for a problem in a state space is formulated by a ___________ a) Intermediate states b) Initial state c) Successor function, which takes current action and returns next immediate state d) None of the mentioned

Last Answer : c) Successor function, which takes current action and returns next immediate state

In LISP, the function evaluates both and is _____________ a) set b) setq c) add d) eva

Description : In LISP, the function evaluates both and is _____________ a) set b) setq c) add d) eva

Last Answer : a) set

Strong Artificial Intelligence is __________ a) the embodiment of human intellectual capabilities within a computer b) a set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans c) the study of mental faculties through the use of mental models implemented on a computer d) all of the mentioned

Description : Strong Artificial Intelligence is __________ a) the embodiment of human intellectual capabilities within a computer b) a set of computer programs that produce output that would be considered to reflect ... through the use of mental models implemented on a computer d) all of the mentioned

Last Answer : a) the embodiment of human intellectual capabilities within a computer

The crossover points of a membership function are defined as the elements in the universe for which a particular fuzzy set has values equal to A. infinite B. 1 C. 0 D. 0.5

Description : The crossover points of a membership function are defined as the elements in the universe for which a particular fuzzy set has values equal to A. infinite B. 1 C. 0 D. 0.5

Last Answer : D. 0.5

The membership values of the membership function are nor strictly monotonically increasing or decreasing or strictly monoronically increasing than decreasing. A. Convex Fuzzy Set B. Non convex fuzzy set C. Normal Fuzzy set D. Sub normal fuzzy set

Description : The membership values of the membership function are nor strictly monotonically increasing or decreasing or strictly monoronically increasing than decreasing. A. Convex Fuzzy Set B. Non convex fuzzy set C. Normal Fuzzy set D. Sub normal fuzzy set

Last Answer : B. Non convex fuzzy set

A fuzzy set has a membership function whose membership values are strictly monotonically increasing or strictly monotonically decreasing or strictly monotonically increasing than strictly monotonically decreasing with increasing values for elements in the universe A. convex fuzzy set B. concave fuzzy set C. Non concave Fuzzy set D. Non Convex Fuzzy set

Description : A fuzzy set has a membership function whose membership values are strictly monotonically increasing or strictly monotonically decreasing or strictly monotonically increasing than strictly monotonically decreasing with increasing ... fuzzy set C. Non concave Fuzzy set D. Non Convex Fuzzy set

Last Answer : A. convex fuzzy set

A fuzzy set wherein no membership function has its value equal to 1 is called A. normal fuzzy set B. subnormal fuzzy set. C. convex fuzzy set D. concave fuzzy set

Description : A fuzzy set wherein no membership function has its value equal to 1 is called A. normal fuzzy set B. subnormal fuzzy set. C. convex fuzzy set D. concave fuzzy set

Last Answer : B. subnormal fuzzy set.

In a Fuzzy set a prototypical element has a value A. 1 B. 0 C. infinite D. Not defined

Description : In a Fuzzy set a prototypical element has a value A. 1 B. 0 C. infinite D. Not defined

Last Answer : A. 1

Membership function defines the fuzziness in a fuzzy set irrespective of the elements in the set, which are discrete or continuous. A. True B. False

Description : Membership function defines the fuzziness in a fuzzy set irrespective of the elements in the set, which are discrete or continuous. A. True B. False

Last Answer : B. False

Transparency A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Transparency A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : C. Worth of the output of a machine learning program that makes it understandable for humans

Vector A. It do not need the control of the human operator during their execution B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars C. The validation of a theory on the basis of a finite number of examples D. None of these

Description : Vector A. It do not need the control of the human operator during their execution B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars C. The validation of a theory on the basis of a finite number of examples D. None of these

Last Answer : B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars

Shallow knowledge A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Shallow knowledge A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : B. The information stored in a database that can be, retrieved with a single query

Search space A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query. C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Search space A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query. C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : A . The large set of candidate solutions possible for a problem

extendible architecture is A. Modular design of a software application that facilitates the integration of new modules B. Showing a universal law or rule to be invalid by providing a counter example C. A set of attributes in a database table that refers to data in another table D. None of these

Description : extendible architecture is A. Modular design of a software application that facilitates the integration of new modules B. Showing a universal law or rule to be invalid by providing a counter example C. ... of attributes in a database table that refers to data in another table D. None of these

Last Answer : A. Modular design of a software application that facilitates the integration of new modules

Falsification is A. Modular design of a software application that facilitates the integration of new modules B. Showing a universal law or rule to be invalid by providing a counter example C. A set of attributes in a database table that refers to data in another table D. None of these

Description : Falsification is A. Modular design of a software application that facilitates the integration of new modules B. Showing a universal law or rule to be invalid by providing a counter example C. A set of attributes in a database table that refers to data in another table D. None of these

Last Answer : B. Showing a universal law or rule to be invalid by providing a counter example

What takes input as an object described by a set of attributes? a) Tree b) Graph c) Decision graph d) Decision tree

Description : What takes input as an object described by a set of attributes? a) Tree b) Graph c) Decision graph d) Decision tree

Last Answer : d) Decision tree

This set of Artificial Intelligence MCQs focuses on “Neural Networks – 2”. 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : This set of Artificial Intelligence MCQs focuses on Neural Networks - 2 . 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in ... by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Description : Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Last Answer : d) All of the mentioned

______ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Description : ______ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Last Answer : c) Fuzzy Set

There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. a) Hedges b) Lingual Variable c) Fuzz Variable d) None of the mentione

Description : There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. a) Hedges b) Lingual Variable c) Fuzz Variable d) None of the mentione

Last Answer : a) Hedges

Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND b) OR c) NOT d) EX-OR

Description : Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND b) OR c) NOT d) EX-OR

Last Answer : a) AND b) OR c) NOT