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## Artificial Intelligence MCQ Set 1

1. The rule of Universal Instantiation (UI for short) says that we can infer any sentence obtained by substituting a ground term (a term without variables) for the variable.
a) True
b) False

Answer: a [Reason:] Rule of universal instantiation.

2. The corresponding Existential Instantiation rule: for the existential quantifier is slightly more complicated. For any sentence a, variable v, and constant symbol k that does not appear elsewhere in the knowledge base
a) True
b) False

Answer: a [Reason:] Rule of existential instantiation.

3. What among the following could the universal instantiation of ___________
For all x King(x) ^ Greedy(x) => Evil(x)
a) King(John) ^ Greedy(John) => Evil(John)
b) King(y) ^ Greedy(y) => Evil(y)
c) King(Richard) ^ Greedy(Richard) => Evil(Richard)
d) All of the mentioned

Answer: d [Reason:] Refer the definition if universal instantiation.

4. Lifted inference rules require finding substitutions that make different logical expressions looks identical.
a) Existential Instantiation
b) Universal Instantiation
c) Unification
d) Modus Ponen

5. Which of the following is not the style of inference?
a) Forward Chaining
b) Backward Chaining
c) Resolution Refutation
d) Modus Ponen

Answer: d [Reason:] Modus ponen is a rule for an inference.

6. In order to utilize generalized Modus Ponens, all sentences in the KB must be in the form of Horn sentences.
a) True
b) False

7. For resolution to apply, all sentences must be in conjunctive normal form, a conjunction of disjunctions of literals.
a) True
b) False

8. Two basic types of inferences are
1. ____________
2. ____________
a) Reduction to propositional logic, Manipulate rules directly
b) Reduction to propositional logic, Apply modus ponen
c) Apply modus ponen, Manipulate rules directly
d) Convert every rule to Horn Clause, Reduction to propositional logic

9. What among the following could the Existential instantiation of
d) None of the mentioned

10. Translate the following statement into FOL.
“For every a, if a is a PhD student, then a has a master degree”
a) ∀ a PhD(a) -> Master(a)
b) ∃ a PhD(a) -> Master(a)
c) A is true, B is true
d) A is false, B is false

## Artificial Intelligence MCQ Set 2

1. Nils Nilsson headed a team at SRI that created a mobile robot named:
a) Robotics
b) Dedalus
c) Shakey
d) Vax

2. An Artificial Intelligence technique that allows computers to understand associations and relationships between objects and events is called:
a) heuristic processing
b) cognitive science
c) relative symbolism
d) pattern matching

3. The new organization established to implement the Fifth Generation Project is called:
a) ICOT (Institute for New Generation Computer Technology)
b) MITI (Ministry of International Trade and Industry)
c) MCC (Microelectronics and Computer Technology Corporation)
d) SCP (Strategic Computing Program)

4. The field that investigates the mechanics of human intelligence is:
a) history
b) cognitive science
c) psychology
d) sociology

5. What is the name of the computer program that simulates the thought processes of human beings?
a) Human logic
b) Expert reason
c) Expert system
d) Personal information

6. What is the name of the computer program that contains the distilled knowledge of an expert?
a) Data base management system
b) Management information System
c) Expert system
d) Artificial intelligence

7. Claude Shannon described the operation of electronic switching circuits with a system of mathematical logic called:
a) LISP
b) XLISP
c) Neural networking
d) Boolean algebra

8. A computer program that contains expertise in a particular domain is called an:
a) intelligent planner
b) automatic processor
c) expert system
d) operational symbolizer

9. What is the term used for describing the judgmental or commonsense part of problem solving?
a) Heuristic
b) Critical
c) Value based
d) Analytical

10. What was originally called the “imitation game” by its creator?
a) The Turing Test
b) LISP
c) The Logic Theorist
d) Cybernetics

11. Decision support programs are designed to help managers make:
a) budget projections
b) visual presentations
d) vacation schedules

12. Programming a robot by physically moving it through the trajectory you want it to follow is called:
a) contact sensing control
b) continuous-path control
c) robot vision control
d) pick-and-place control

## Artificial Intelligence MCQ Set 3

1. In many problems the path to goal is irrelevant, this class of problems can be solved using,
a) Informed Search Techniques
b) Uninformed Search Techniques
c) Local Search Techniques
d) Informed & Uninformed Search Techniques

Answer: c [Reason:] If the path to the goal does not matter, we might consider a different class of algorithms, ones that do not worry about paths at all. Local search algorithms operate using a single current state (rather than multiple paths) and generally move only to neighbors of that state.

2. Though local search algorithms are not systematic, key advantages would include
a) Less memory
b) More time
c) Finds a solution in large infinite space
d) Less memory & Finds a solution in large infinite space

Answer: d [Reason:] Two advantages: (1) they use very little memory-usually a constant amount; and (2) they can often find reasonable solutions in large or infinite (continuous) state spaces for which systematic algorithms are unsuitable.

3. A complete, local search algorithm always finds goal if one exists, an optimal algorithm always finds a global minimum/maximum. State whether True or False.
a) True
b) False

Answer: a [Reason:] An algorithm is complete if it finds a solution if exists and optimal if finds optimal goal (minimum or maximum)

4. _______________ Is an algorithm, a loop that continually moves in the direction of increasing value – that is uphill
a) Up-Hill Search
b) Hill-Climbing
c) Hill algorithm
d) Reverse-Down-Hill search

Answer: b [Reason:] Refer the definition of Hill-Climbing approach.

5. Hill-Climbing algorithm terminates when,
a) Stopping criterion met
b) Global Min/Max is achieved
c) No neighbor has higher value
d) All of the mentioned

Answer: c [Reason:] When no neighbor is having higher value, algorithm terminates fetching local min/max.

6. One of the main cons of hill-climbing search is,
a) Terminates at local optimum & Does not find optimum solution
b) Terminates at global optimum & Does not find optimum solution
c) Does not find optimum solution & Fail to find a solution
d) Fail to find a solution

Answer: a [Reason:] Algorithm terminates at local optimum values, hence fails to find optimum solution.

7. Stochastic hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphil1 move.
a) True
b) False

Answer: a [Reason:] Refer to the definition of variants of hill-climbing search.

8. Hill climbing sometimes called ____________ because it grabs a good neighbor state without thinking ahead about where to go next.
a) Needy local search
b) Heuristic local search
c) Greedy local search
d) Optimal local search

9. Hill-Climbing approach stuck for the following reasons
a) Local maxima
b) Ridges
c) Plateaux
d) All of the menttioned

Answer: d [Reason:] Local maxima: a local maximum is a peak that is higher than each of its neighboring states, but lower than the global maximum. Ridges: Ridges result in a sequence of local maxima that is very difficult for greedy algorithms to navigate. Plateaux: a plateau is an area of the state space landscape where the evaluation function is flat.

10. ___________ algorithm keeps track of k states rather than just one.
a) Hill-Climbing search
b) Local Beam search
c) Stochastic hill-climbing search
d) Random restart hill-climbing search

Answer: b [Reason:] Refer to the definition of Local Beam Search algorithm.

11. A genetic algorithm (or GA) is a variant of stochastic beam search in which successor states are generated by combining two parent states, rather than by modifying a single state.
a) True
b) False

Answer: a [Reason:] Stochastic beam search, analogous to stochastic hill climbing, helps to alleviate this problem. Instead of choosing the best k from the pool of candidate successors, stochastic beam search chooses k successors at random, with the probability of choosing a given successor being an increasing function of its value.

12. Mark two main features of Genetic Algorithm
a) Fitness function & Cross-over techniques
b) Cross-over techniques & Random mutation
c) Individuals among the population & Random mutation
d) Random mutation & Fitness function

Answer: a [Reason:] Fitness function helps choosing individuals from the population and Cross-over techniques defines the off-spring generated.

13. Searching using query on Internet is, use of ___________ type of agent
a) Offline agent
b) Online agent
c) Both Offline & Online agent
d) Goal Based & Online agent

Answer: d [Reason:] Refer to the definitions of both the type of agent.

## Artificial Intelligence MCQ Set 4

1. A series of Artificial Intelligence systems, developed by Pat Langley to explore the role of heuristics in scientific discovery is ________
a) RAMD
b) BACON
c) MIT
d) DU

2. A.M. turing developed a technique for determining whether a computer could or could not demonstrate the artificial Intelligence, Presently, this technique is called
a) Turing Test
b) Algorithm
c) Boolean Algebra
d) Logarithm

3. A Personal Consultant knowledge base contain information in the form of:
a) parameters
b) contexts
c) production rules
d) all of the mentioned

4. Which approach to speech recognition avoids the problem caused by the variation in speech patterns among different speakers?
a) Continuous speech recognition
b) Isolated word recognition
c) Connected word recognition
d) Speaker-dependent recognition

5. Which of the following, is a component of an expert system?
a) inference engine
b) knowledge base
c) user interface
d) all of the mentioned

6. A computer vision technique that relies on image templates is:
a) edge detection
b) binocular vision
c) model-based vision
d) robot vision

7. DARPA, the agency that has funded a great deal of American Artificial Intelligence research, is part of the Department of:
a) Defense
b) Energy
c) Education
d) Justice

8. Which of these schools was not among the early leaders in Artificial Intelligence research?
a) Dartmouth University
b) Harvard University
c) Massachusetts Institute of Technology
d) Stanford University

9. A certain Professor at the Stanford University coined the word ‘artificial intelligence’ in 1956 at a conference held at Dartmouth college. Can you name the Professor?
a) David Levy
b) John McCarthy
c) Joseph Weizenbaum
d) Hans Berliner

10. In LISP, the function (copy-list <list>)
a) returns a new list that is equal to <list> by copying the top-level element of <list>
b) returns the length of <list>
c) returns t if <list> is empty
d) all of the mentioned

11. Who is the “father” of artificial intelligence?
b) John McCarthy
c) Allen Newell
d) Alan Turning

12. In 1985, the famous chess player David Levy beat a world champion chess program in four straight games by using orthodox moves that confused the program. What was the name of the chess program?
a) Kaissa
b) CRAY BLITZ
c) Golf
d) DIGDUG

13. The explanation facility of an expert system may be used to:
a) construct a diagnostic model
b) expedite the debugging process
c) explain the system’s reasoning process
d) expedite the debugging process & explain the system’s reasoning process

14. A process that is repeated, evaluated, and refined is called:
a) diagnostic
b) descriptive
c) interpretive
d) iterative

15. Visual clues that are helpful in computer vision include:
a) color and motion
b) depth and texture
c) height and weight
d) color and motion, depth and texture

## Artificial Intelligence MCQ Set 5

1. Ambiguity may be caused by:
a) syntactic ambiguity
b) multiple word meanings
c) unclear antecedents
d) all of the mentioned

2. Which company offers the LISP machine considered “the most powerful symbolic processor available”?
a) LMI
b) Symbolics
c) Xerox
d) Texas Instruments

3. What of the following is considered a pivotal event in the history of Artificial Intelligence?
a) 1949, Donald O, The organization of Behavior
b) 1950, Computing Machinery and Intelligence
c) 1956, Dartmouth University Conference Organized by John McCarthy
d) 1961, Computer and Computer Sense

4. Natural language processing is divided into the two sub-fields of:
a) symbolic and numeric
b) time and motion
c) algorithmic and heuristic
d) understanding and generation

5. High-resolution, bit-mapped displays are useful for displaying:
a) clearer characters
b) graphics
c) more characters
d) all of the mentioned

6. A bidirectional feedback loop links computer modeling with:
a) artificial science
b) heuristic processing
c) human intelligence
d) cognitive science

7. Which of the following have people traditionally done better than computers?
a) recognizing relative importance
b) finding similarities
c) resolving ambiguity
d) all of the mentioned

8. In LISP, the function evaluates both and is
a) set
b) setq
d) eva

9. Which type of actuator generates a good deal of power but tends to be messy?
a) electric
b) hydraulic
c) pneumatic
d) both hydraulic & pneumatic

10. Research scientists all over the world are taking steps towards building computers with circuits patterned after the complex inter connections existing among the human brain’s nerve cells. What name is given to such type of computers?
a) Intelligent computers
b) Supercomputers
c) Neural network computers
d) Smart computers

11. The integrated circuit was invented by Jack Kilby of:
a) MIT
b) Texas Instruments
c) Xerox
d) All of the mentioned

12. People overcome natural language problems by:
a) grouping attributes into frames
b) understanding ideas in context
c) identifying with familiar situations
d) both understanding ideas in context & identifying with familiar situations

13. The Cedar, BBN Butterfly, Cosmic Cube and Hypercube machine can be characterized as
a) SISD
b) MIMD
c) SIMD
d) MISD

14. A series of AI systems, developed by Pat Langley to explore the role of heuristics in scientific discovery is ________
a) RAMD
b) BACON
c) MIT
d) DU

## Artificial Intelligence MCQ Set 6

1. Which is not a desirable property of a logical rule-based system?
a) Locality
b) Attachment
c) Detachment
d) Truth-Functionality

Answer: b [Reason:] Locality: In logical systems, whenever we have a rule of the form A => B, we can conclude B, given evidence A, without worrying about any other rules. Detachment: Once a logical proof is found for a proposition B, the proposition can be used regardless of how it was derived .That is, it can be detachment from its justification. Truth-functionality: In logic, the truth of complex sentences can be computed from the truth of the components. However, there are no Attachment properties lies in a Rule-based system. Global attribute defines a particular problem space as user specific and changes according to user’s plan to problem.

2. How is Fuzzy Logic different from conventional control methods?
a) IF and THEN Approach
b) FOR Approach
c) WHILE Approach
d) DO Approach

Answer: a [Reason:] FL incorporates a simple, rule-based IF X AND Y THEN Z approach to a solving control problem rather than attempting to model a system mathematically.

3. In an Unsupervised learning
a) Specific output values are given
b) Specific output values are not given
c) No specific Inputs are given
d) Both inputs and outputs are given

Answer: b [Reason:] The problem of unsupervised learning involves learning patterns in the input when no specific output values are supplied. We cannot expect the specific output to test your result. Here the agent does not know what to do, as he is not aware of the fact what propose system will come out. We can say an ambiguous un-proposed situation.

4. Inductive learning involves finding a
a) Consistent Hypothesis
b) Inconsistent Hypothesis
c) Regular Hypothesis
d) Irregular Hypothesis

Answer: a [Reason:] Inductive learning involves finding a consistent hypothesis that agrees with examples. The difficulty of the task depends on the chosen representation.

5. Computational learning theory analyzes the sample complexity and computational complexity of
a) Unsupervised Learning
b) Inductive learning
c) Forced based learning
d) Weak learning

Answer: b [Reason:] Computational learning theory analyzes the sample complexity and computational complexity of inductive learning. There is a tradeoff between the expressiveness of the hypothesis language and the ease of learning.

6. If a hypothesis says it should be positive, but in fact, it is negative, we call it
a) A consistent hypothesis
b) A false negative hypothesis
c) A false positive hypothesis
d) A specialized hypothesis

Answer: c [Reason:] Consistent hypothesis go with examples, If the hypothesis says it should be negative but infect it is positive, it is false negative. If a hypothesis says it should be positive, but in fact, it is negative, it is false positive. In a specialized hypothesis we need to have certain restrict or special conditions.

7. Neural Networks are complex ______________with many parameters.
a) Linear Functions
b) Nonlinear Functions
c) Discrete Functions
d) Exponential Functions

Answer: b [Reason:] Neural networks parameters can be learned from noisy data and they have been used for thousands of applications, so it varies from problem to problem and thus use nonlinear functions.

8. A perceptron is a ______________
a) Feed-forward neural network
b) Back-propagation algorithm
c) Back-tracking algorithm
d) Feed Forward-backward algorithm

Answer: a [Reason:] A perceptron is a Feed-forward neural network with no hidden units that can be representing only linear separable functions. If the data are linearly separable, a simple weight updated rule can be used to fit the data exactly.

9. Which of the following statement is true?
a) Not all formal languages are context-free
b) All formal languages are Context free
c) All formal languages are like natural language
d) Natural languages are context-oriented free

Answer: a [Reason:] Not all formal languages are context-free.

10. Which of the following statement is not true?
a) The union and concatenation of two context-free languages is context-free
b) The reverse of a context-free language is context-free, but the complement need not be
c) Every regular language is context-free because it can be described by a regular grammar
d) The intersection two context-free languages is context-free

Answer: d [Reason:] The union and concatenation of two context-free languages is context-free; but intersection need not be.

## Artificial Intelligence MCQ Set 7

1. In LISP, the function (minusp (-20 4 8 8 1) returns
a) T
b) F
c) NIL
d) -20

2. In LISP, which of the following function assigns the value 10 to the symbol a?
a) (setq a 10)
b) (a = b) where b = 10
c) (a = 10) (d) (setq 10 a)
d) All of the mentioned

3. In LISP, the atom that stands for “False” is
a) t
b) nil
c) y
d) time

4. The expert system developed at MIT to solve mathematical problems is known as:
a) RAND
b) ISIS
c) MACSYMA
d) MOLGEN

5. Which approach to speech recognition avoids the problem caused by the differences in the way words are pronounced according to context?
a) continuous speech recognition
b) connected word recognition
c) isolated word recognition
d) speaker-dependent recognition

6. A KES knowledge base contains information in the form of:
a) associations
b) actions
c) free text
d) all of the mentioned

7. In AI programming, a list may contain:
a) cells
b) fields
c) pointers
d) all of the mentioned

8. In LISP, the function (minusp (-20 4 8 8 1) returns
a) T
b) F
c) NIL
d) -20

9. Special programs that assist programmers are called:
a) heuristic processors
b) symbolic programmers
c) intelligent programming tools
d) program recognizers

10. If the English Philosopher Thomas Hobbes could be called ‘grandfather’ of artificial intelligence, then who could be called its father?
a) A.M. Turning
b) John McCarthy
c) Allen Newell
d) Herbert Simon

## Artificial Intelligence MCQ Set 8

1. Given a stream of text, Named Entity Recognition determines which pronoun maps to which noun.
a) False
b) True

Answer: a [Reason:] Given a stream of text, Named Entity Recognition determines which items in the text maps to proper names.

2. Natural Language generation is the main task of Natural language processing.
a) True
b) False

Answer: a [Reason:] Natural Language Generation is to Convert information from computer databases into readable human language.

3. OCR (Optical Character Recognition) uses NLP.
a) True
b) False

Answer: a [Reason:] Given an image representing printed text, determines the corresponding text.

4. Parts-of-Speech tagging determines
a) part-of-speech for each word dynamically as per meaning of the sentence
b) part-of-speech for each word dynamically as per sentence structure
c) all part-of-speech for a specific word given as input
d) all of the mentioned

Answer: d [Reason:] A Bayesian network provides a complete description of the domain.

5. Parsing determines Parse Trees (Grammatical Analysis) for a given sentence.
a) True
b) False

Answer: a [Reason:] Determine the parse tree (grammatical analysis) of a given sentence. The grammar for natural languages is ambiguous and typical sentences have multiple possible analyses. In fact, perhaps surprisingly, for a typical sentence there may be thousands of potential parses (most of which will seem completely nonsensical to a human).

6. IR (information Retrieval) and IE (Information Extraction) are the two same thing.
a) True
b) False

Answer: b [Reason:] Information retrieval (IR) This is concerned with storing, searching and retrieving information. It is a separate field within computer science (closer to databases), but IR relies on some NLP methods (for example, stemming). Some current research and applications seek to bridge the gap between IR and NLP. Information extraction (IE) This is concerned in general with the extraction of semantic information from text. This covers tasks such as named entity recognition, Coreference resolution, relationship extraction, etc.

7. Many words have more than one meaning; we have to select the meaning which makes the most sense in context. This can be resolved by
a) Fuzzy Logic
b) Word Sense Disambiguation
c) Shallow Semantic Analysis
d) All of the mentioned

Answer: b [Reason:] Shallow Semantic Analysis doesn’t cover word sense disambiguation.

8. Given a sound clip of a person or people speaking, determine the textual representation of the speech.
a) Text-to-speech
b) Speech-to-text
c) All of the mentioned
d) None of the mentioned

Answer: b [Reason:] NLP is required to linguistic analysis.

9. Speech Segmentation is a subtask of Speech Recognition.
a) True
b) False