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This section includes 210 Mcqs, each offering curated multiple-choice questions to sharpen your Artificial Intelligence knowledge and support exam preparation. Choose a topic below to get started.
101. |
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» E. | |
102. |
Inference algorithm is complete only if, |
A. | It can derive any sentence |
B. | It can derive any sentence that is an entailed version |
C. | It is truth preserving |
D. | It can derive any sentence that is an entailed version & It is truth preserving |
Answer» E. | |
103. |
‘α |= β ‘(to mean that the sentence α entails the sentence β) if and only if, in every model in which α is _____ β is also _____ |
A. | True, true |
B. | True, false |
C. | False, true |
D. | False, false |
Answer» B. True, false | |
104. |
Wumpus World is a classic problem, best example of ____ |
A. | Single player Game |
B. | Two player Game |
C. | Reasoning with Knowledge |
D. | Knowledge based Game |
Answer» D. Knowledge based Game | |
105. |
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 |
Answer» B. A is false, B is false | |
106. |
What form of negation does the prolog allows? |
A. | Negation as failure |
B. | Proposition |
C. | Substitution |
D. | Negation as success |
Answer» B. Proposition | |
107. |
Which is omitted in prolog unification algorithm? |
A. | Variable check |
B. | Occur check |
C. | Proposition check |
D. | Both Occur & Proposition check |
Answer» C. Proposition check | |
108. |
How many possible sources of complexity are there in forward chaining? |
A. | 1 |
B. | 2 |
C. | 3 |
D. | 4 |
Answer» D. 4 | |
109. |
When the resolution is called as refutation-complete? |
A. | Sentence is satisfiable |
B. | Sentence is unsatisfiable |
C. | Sentence remains the same |
D. | None of the mentioned |
Answer» C. Sentence remains the same | |
110. |
What will happen if two literals are identical? |
A. | Remains the same |
B. | Added as three |
C. | Reduced to one |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
111. |
What kind of clauses are available in Conjunctive Normal Form ? |
A. | Disjunction of literals |
B. | Disjunction of variables |
C. | Conjunction of literals |
D. | Conjunction of variables |
Answer» B. Disjunction of variables | |
112. |
What can be viewed as single lateral of disjunction ? |
A. | Multiple clause |
B. | Combine clause |
C. | Unit clause |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
113. |
Which form is called as conjunction of disjunction of literals? |
A. | Conjunctive normal form |
B. | Disjunctive normal form |
C. | Normal form |
D. | All of the mentioned |
Answer» B. Disjunctive normal form | |
114. |
What can be viewed as single lateral of disjunction? |
A. | Multiple clause |
B. | Combine clause |
C. | Unit clause |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
115. |
The adjective “first-order” distinguishes first-order logic from ___________ in which there are predicates having predicates or functions as arguments, or in which one or both of predicate quantifiers or function quantifiers are permitted. |
A. | Representational Verification |
B. | Representational Adequacy |
C. | Higher Order Logic |
D. | Inferential Efficiency |
Answer» D. Inferential Efficiency | |
116. |
Translate the following statement into FOL. “For every a, if a is a philosopher, then a is a scholar” |
A. | ∀ a philosopher(a) scholar(a) |
B. | ∃ a philosopher(a) scholar(a) |
C. | All of the mentioned |
D. | None of the mentioned |
Answer» B. ∃ a philosopher(a) scholar(a) | |
117. |
Which function is used to calculate the feasibility of whole game tree? |
A. | Evaluation function |
B. | Transposition |
C. | Alpha-beta pruning |
D. | All of the mentioned |
Answer» B. Transposition | |
118. |
Which is identical to the closed list in Graph search? |
A. | Hill climbing search algorithm |
B. | Depth-first search |
C. | Transposition table |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
119. |
Which search is equal to minimax search but eliminates the branches that can’t influence the final decision? |
A. | Depth-first search |
B. | Breadth-first search |
C. | Alpha-beta pruning |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
120. |
Which approach is to pretend that a pure divide and conquer algorithm will work? |
A. | Goal independence |
B. | Subgoal independence |
C. | Both Goal & Subgoal independence |
D. | None of the mentioned |
Answer» C. Both Goal & Subgoal independence | |
121. |
What is the other name of backward state-space search? |
A. | Regression planning |
B. | Progression planning |
C. | State planning |
D. | Test planning |
Answer» B. Progression planning | |
122. |
The complexity of minimax algorithm is |
A. | Same as of DFS |
B. | Space – bm and time – bm |
C. | Time – bm and space – bm |
D. | Same as BFS |
Answer» B. Space – bm and time – bm | |
123. |
General algorithm applied on game tree for making decision of win/lose is _______ |
A. | DFS/BFS Search Algorithms |
B. | Heuristic Search Algorithms |
C. | Greedy Search Algorithms |
D. | MIN/MAX Algorithms |
Answer» E. | |
124. |
Which of the following algorithm is generally used CSP search algorithm? |
A. | Breadth-first search algorithm |
B. | Depth-first search algorithm |
C. | Hill-climbing search algorithm |
D. | None of the mentioned |
Answer» C. Hill-climbing search algorithm | |
125. |
When do we call the states are safely explored? |
A. | A goal state is unreachable from any state |
B. | A goal state is denied access |
C. | A goal state is reachable from every state |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
126. |
Backtracking is based on, |
A. | Last in first out |
B. | First in first out |
C. | Recursion |
D. | Both Last in first out & Recursion |
Answer» E. | |
127. |
Language/Languages used for programming Constraint Programming includes |
A. | Prolog |
B. | C# |
C. | c |
D. | Fortrun |
Answer» B. C# | |
128. |
Flexible CSPs relax on _______ |
A. | Constraints |
B. | Current State |
C. | Initial State |
D. | Goal State |
Answer» B. Current State | |
129. |
____________ 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 |
Answer» C. Flexible CSPs | |
130. |
Solving a constraint satisfaction problem on a finite domain is an/a ___________ problem with respect to the domain size. |
A. | P complete |
B. | NP complete |
C. | NP hard |
D. | Domain dependent |
Answer» C. NP hard | |
131. |
Constraint satisfaction problems on finite domains are typically solved using a form of ___________ |
A. | Search Algorithms |
B. | Heuristic Search Algorithms |
C. | Greedy Search Algorithms |
D. | All of the mentioned |
Answer» E. | |
132. |
To overcome the need to backtrack in constraint satisfaction problem can be eliminated by |
A. | Forward Searching |
B. | Constraint Propagation |
C. | Backtrack after a forward search |
D. | Omitting the constraints and focusing only on goals |
Answer» B. Constraint Propagation | |
133. |
Consider a problem of preparing a schedule for a class of student. This problem is a type of |
A. | Search Problem |
B. | Backtrack Problem |
C. | CSP |
D. | Planning Problem |
Answer» D. Planning Problem | |
134. |
The term ___________ is used for a depth-first search that chooses values for one variable at a time and returns when a variable has no legal values left to assign. |
A. | Forward search |
B. | Backtrack search |
C. | Hill algorithm |
D. | Reverse-Down-Hill search |
Answer» C. Hill algorithm | |
135. |
What among the following constitutes to the incremental formulation of CSP? |
A. | Path cost |
B. | Goal cost |
C. | Successor function |
D. | All of the mentioned |
Answer» E. | |
136. |
Which of the Following problems can be modeled as CSP? |
A. | 8-Puzzle problem |
B. | 8-Queen problem |
C. | Map coloring problem |
D. | All of the mentioned |
Answer» E. | |
137. |
_________________ 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 |
Answer» B. Uninformed Search Problems | |
138. |
Random mutation & Fitness function |
A. | Offline agent |
B. | Online agent |
C. | Both Offline & Online agent |
D. | Goal Based & Online agent |
Answer» E. | |
139. |
___________ 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» C. Stochastic hill-climbing search | |
140. |
Hill-Climbing approach stuck for the following reasons |
A. | Local maxima |
B. | Ridges |
C. | Plateaux |
D. | All of the mentioned |
Answer» E. | |
141. |
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 |
Answer» D. Optimal local search | |
142. |
______________ 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» C. Hill algorithm | |
143. |
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» D. Informed & Uninformed Search Techniques | |
144. |
Greedy search strategy chooses the node for expansion |
A. | Shallowest |
B. | Deepest |
C. | The one closest to the goal node |
D. | Minimum heuristic cost |
Answer» D. Minimum heuristic cost | |
145. |
In greedy approach evaluation function is |
A. | Heuristic function |
B. | Path cost from start node to current node |
C. | Path cost from start node to current node + Heuristic cost |
D. | Average of Path cost from start node to current node and Heuristic cost |
Answer» B. Path cost from start node to current node | |
146. |
What is the space complexity of Greedy search? |
A. | O(b) |
B. | O(bl) |
C. | O(m) |
D. | O(bm) |
Answer» E. | |
147. |
Heuristic function h(n) is ____ |
A. | Lowest path cost |
B. | Cheapest path from root to goal node |
C. | Estimated cost of cheapest path from root to goal node |
D. | Average path cost |
Answer» D. Average path cost | |
148. |
Which search method will expand the node that is closest to the goal? |
A. | Best-first search |
B. | Greedy best-first search |
C. | A* search |
D. | None of the mentioned |
Answer» C. A* search | |
149. |
Which is used to improve the performance of heuristic search ? |
A. | Quality of nodes |
B. | Quality of heuristic function |
C. | Simple form of nodes |
D. | None of the mentioned |
Answer» C. Simple form of nodes | |
150. |
Which is used to improve the performance of heuristic search? |
A. | Quality of nodes |
B. | Quality of heuristic function |
C. | Simple form of nodes |
D. | None of the mentioned |
Answer» C. Simple form of nodes | |