Q2➡| NTA UGC NET December 2021 Consider the sentence below. There is a country that borders both India and Pakistan. Which of the following logical expressions express the above sentence correctly when the predicate Country(x) represents that x is a country and Borders(x, y) represents that the countries x and y share the border?
i ➥[∃c Country(c)] ⇒ [Border (c, India) ∧ Border (c,Pakistan)]
ii ➥ ∃c Border (Country(c), India ∧ Pakistan)
iii ➥∃c Country(c) ∧ Border (c, India) ∧ Border (c,Pakistan)
iv ➥∃c Country(c) ⇒ [Border (c, India) ∧ Border (c,Pakistan)]
Q3➡| NTA UGC NET December 2021 Which among the following statement(s) is(are) FALSE? A. Greedy best-first search is not optimal but is often efficient. B. A* is complete and optimal provided h(n) is admissible or consistent. C. Recursive best-first search is efficient in terms of time complexity but poor in terms of space complexity. D. h(n) = 0 is an admissible heuristic for the 8-puzzle.
Q4➡| NTA UGC NET December 2021 Given below are two statements Statement I: Breadth-First Search is optimal when all the step costs are equal whereas uniform-cost se optimal with any step-cost. Statement II: When all the step costs are same uniform-cost search expends more nodes at depth d tha Breadth-First Search. In light of the above statements, choose the correct answer from the options given below
i ➥Both Statement I and Statement II are false
ii ➥ Both Statement I and Statement II are true
iii ➥Statement I is false but Statement II is true
Q6➡| NTA UGC NET December 2021 Next five questions are based on the following passage. Consider a domain consisting of three Boolean variables Toothache, Cavity, and Catch. The full joint distribution is a 2×2×2 table as shown in the figure below. The probability of a toothache, given evidence of a cavity, P(toothache | cavity) is ____.
i ➥0.216
ii ➥ 0.280
iii ➥0.400
iv ➥0.600
Show Answer With Best Explanation
Answer: IV Explanation: Formula, Conditional Probability Calculation, The probability of a toothache, given evidence of a cavity, P(toothache Ո cavity ) = 0.108 + 0.012 = 0.12
Q7➡| NTA UGC NET December 2021 Next five questions are based on the following passage. Consider a domain consisting of three Boolean variables Toothache, Cavity, and Catch. The full joint distribution is a 2×2×2 table as shown in the figure below. P(cavity U toothache) is________________.
i ➥0.120
ii ➥ 0.200
iii ➥0.280
iv ➥ 0.600
Show Answer With Best Explanation
Answer: III Explanation: Formula, P(A U B) = P(A) + P(B) – P(A Ո B) Calculation, P(cavity U toothache) = P(cavity) + P(toothache) – P(cavity Ո toothache) P(cavity ) = 0.108 + 0.012 + 0.072 + 0.008 = 0.2
Q8➡| NTA UGC NET December 2021 Next five questions are based on the following passage. Consider a domain consisting of three Boolean variables Toothache, Cavity, and Catch. The full joint distribution is a 2×2×2 table as shown in the figure below. The probability for Cavity, given that either Toothache or Catch is true, P(Cavity | toothache U catch) is _______.
i ➥0.4615
ii ➥ 0.5384
iii ➥0.6000
iv ➥ 0.8000
Show Answer With Best Explanation
Answer: I Explanation: Formula, Calculation, P(cavity Ո(toothache U catch)) = 0.108 + 0.012 + 0.072 = 0.192
Q9➡| NTA UGC NET December 2021 Next five questions are based on the following passage. Consider a domain consisting of three Boolean variables Toothache, Cavity, and Catch. The full joint distribution is a 2×2×2 table as shown in the figure below. The marginal probability of cavity P(cavity) is _____.
Q10➡| NTA UGC NET December 2021 Next five questions are based on the following passage. Consider a domain consisting of three Boolean variables Toothache, Cavity, and Catch. The full joint distribution is a 2×2×2 table as shown in the figure below. The probability of a cavity, given evidence of a toothache, P(cavity | toothache) is ____.
i ➥0.216
ii ➥ 0.280
iii ➥0.400
iv ➥ 0.600
Show Answer With Best Explanation
Answer: IV Explanation: Formula, Conditional Probability Calculation, The probability of a cavity, given evidence of a toothache, P(cavityՈtoothache ) = 0.108 + 0.012 = 0.12
Q11➡| NTA UGC NET November 2020 Consider the statement below. A person who is radical (R) is electable (E) if he/she is conservative (C), but otherwise is not electable. Few probable logical assertions of the above sentence are given below. (A) (R∧E)⇔C (B) R→(E↔C) (C) R⇒((C⇒E)∨¬E) (D) (¬R∨¬E∨C)∧(¬R∨¬C∨E) Which of the above logical assertions are true? Choose the correct answer from the options given below:
i ➥ (B) only
ii ➥ (C) only
iii ➥ (A) and (C) only
iv ➥ (B) and (D) only
Show Answer With Best Explanation
Answer: IV Explanation: (A) (R ∧ E) ⇔ C It is not equivalent to above statement. It says that all conservative(C) are Radical(R) and Electable (E). (B) R ⇒ (E ⇔C) It is equivalent to above statement. It says that if all person are Radical(R) then they are Electable (E) if And only if they are Conservative (C). (C) R ⇒ ((C⇒E) v ¬E) R ⇒ (¬C v E v ¬E ) It is tautology, That is it is true in all condition because E is in both form (Normal Form & Complemented Form) (D) (¬R v ¬E v C) ∧ (¬R v ¬ C v E) (¬R v E ⇒C) ∧ (¬R v C ⇒E) ¬R v ((E ⇒C) ∧ (C ⇒E)) ¬R v (E ⇔C) R ⇒ (E ⇔C) It is equivalent to above statement. It says that if all person are Radical(R) then they are Electable (E) if And only if they are Conservative (C).
Q13➡| NTA UGC NET November 2020 Given below are two statements: Statement I: A genetic algorithm is a stochastic hill climbing search in which a large population of states is maintained. Statement II: In a nondeterministic environment, agents can apply AND-OR search to generate containing plans that reach the goal regardless of which outcomes occur during execution. In the light of the above statements, choose the correct answers from the options given below.
i ➥ Both Statement I and Statement II are true
ii ➥ Both Statement I and Statement II are false
iii ➥ Statement I is correct but Statement II is false
iv ➥ Statement I is incorrect but Statement II is true
Show Answer With Best Explanation
Answer: I Explanation: Statement I: Stochastic Hill-climbing as a core Method for Evaluating Genetic Algorithms Stochastic Hill-climbing maintains a vast population of states. next new states are created by mutation and crossover, which put together pairs of states from the population.
Hence Statement I is correct. Statement II: contingent solutions to nondeterministic problems By constructing search trees AI agents use AND-OR search tree in non-deterministic environments to initiate contingent plans that achieve the destination (Target/Goal) regardless of which outcomes occur during execution.
Hence Statement II is also correct. Important points for your exam AND-OR search trees: By constructing search trees we find contingent solutions to nondeterministic problems OR nodes: in deterministic environment, we call nodes OR nodes when the only branching is initiate by the agent’s own choices OR NODE in each state. AND nodes: In a non-deterministic environment, we call nodes OR nodes when branching is initiate by the environment’s choice of outcome for each action. So the Correct Answer is Option (I).
Q14➡| NTA UGC NET November 2020 Which of the following statements are true? A) Minimax search is breadth-first; it processes all the nodes at a level before moving to a node in the next level. B) The effectiveness of the alpha-beta pruning is highly dependent on the order in which the states are examined. C) The alpha-beta search algorithm computes the same optimal moves as the minimax algorithm. D) Optimal play in games of imperfect information does not require reasoning about the current and future belief states of each player. Choose the correct answer from the options given below:
Q15➡| NTA UGC NET November 2020 Which of the following statements are true? A) A sentence α entails another sentence ßifß is true in few words where α is true. B) Forward chaining and backward chaining are very natural reasoning algorithms for knowledge bases in Horn form. C) Sound inference algorithms derive all sentences that are entailed. D) Propositional logic does not scale to environments of unbounded size. Choose the correct answer from the options given below:
Q18➡| NTA UGC NET November 2020 If f(x) = x is my friend, and p(x) = x is perfect then correct logical translation of the statement “some of my friends are not perfect” is__________.
i ➥ ∀ (f(x) ∧ ¬ p(x))
ii ➥ ∃ (f(x) ∧ ¬ p(x))
iii ➥ ¬ (f(x) ∧ ¬ p(x))
iv ➥ ∃ ( ¬ f(x) ∧ ¬ p(x))
Show Answer With Best Explanation
Answer: II Explanation: It is given that, f(x)=x is my friend p(x) = x is perfect statement: some of my friends are not perfect. There exist is used for ‘some’. Outer most part contains ∃x. In statement , condition is ‘not perfect’ . so, we get ^ p(x). Finally we get, ∃x(f(x)∧⌐p(x))
Q21➡| NTA UGC NET December 2019 Let Wo represents weight between node i at layer k and node j at layer (k – 1) of a given multilayer perceptron. The weight updation using gradient descent method is given by
Where α and E represents learning rate and Error in the output respectively?
Q22➡| NTA UGC NET December 2019 Consider the following learning algorithms: (a) Logistic regression (b) Back propagation (c) Linear repression Which of the following option represents classification algorithms?
Q23➡| NTA UGC NET December 2019 Consider the following: (a) Trapping at local maxima (b) Reaching a plateau (c) Traversal along the ridge. Which of the following option represents shortcomings of the hill climbing algorithm?
Q24➡| NTA UGC NET December 2019 An _ chart is a project schedule representation that presents project plan as a directed graph. The critical path is the____________sequence of_________tasks and it defines project __________.
Q27➡| NTA UGC NET June 2019 Consider the following methods: M 1 : mean of maximum M 2 : Centre of area M 3 : Height method Which of the following is/are defuzzification method(s)?
i ➥ Only M 1
ii ➥ Only M 1 and M 2
iii ➥ Only M 2and M 3
iv ➥ M 1 , M 2 and M 3
Show Answer With Best Explanation
Answer: IV Explanation: Defuzzification is the conversion of a fuzzy quantity to a precise quantity. Defuzzification Methods are. 1.Mean of Maxima Method (MOM) 2.Weighted Average Method 3.Centroid of Area(COA) 4.Center of Area 5.Bisector of Area Method (BOA) 6.Center of gravity (COG) 7.Maxima Methods 8.First of Maxima Method (FOM) 9.Last of Maxima Method (LOM) 10.Center of Sums Method (COS) So correct answer is (IV).
Q28➡| NTA UGC NET June 2019 A fuzzy conjunction operator denoted as t(x,y) and fuzzy disjunction operator denoted as s(x,Y) form dual pair if they satisfy the condition:
Q29➡| NTA UGC NET June 2019 Consider the following: (a) Evolution (b) Selection (c) reproduction (d) Mutation Which of the following are found in genetic algorithms?
Q35➡| NTA UGC NET December 2018 Consider the following terminology and match List 1 and List 2 and choose the correct answer from the code given below b= branch factor d= depth of shallowest solution bd M= Maximum depth of the search tree I= depth limit
Q38➡| NTA UGC NET December 2018 Consider the following statements S1: A heuristic is admissible if it never overestimates the cost to reach the goal S2: A heuristic is monotonous if it follows triangle inequality property. Which one of the following is true referencing the above statements?
i ➥ Statement S1 is true but statement S2 is false.
ii ➥ Statement S1 is false but statement S2 is true.
iii ➥ Neither of the statements S1 and S2 are true
Q49➡| Consider the following logical inferences : I1 : If it is Sunday then school will not open. The school was open. Inference : It was not Sunday. I2 : If it is Sunday then school will not open. It was not Sunday. Inference : The school was open. Which of the following is correct?
i ➥ Both I1 and I2 are correct inferences
ii ➥ I1 is correct but I2 is not a correct inference
iii ➥ I1 is not correct but I2 is a correct inference
Q56➡| Means-Ends Analysis process centres around the detection of difference between the current state and the goal state. Once such a difference is found, then to reduce the difference one applies ………………
i ➥ a forward search that can reduce the difference.
ii ➥ a backward search that can reduce the difference
iii ➥ a bidirectional search that can reduce the difference.
Q57➡| An A* algorithm is a heuristic search technique which
i ➥ is like a depth-first search where most promising child is selected for expansion
ii ➥ generates all successor nodes and computes an estimate of distance (cost) from start node to a goal node through each of the successors. It then chooses the successor with shortest cost.
iii ➥ saves all path lengths (costs) from start node to all generated nodes and chooses shortest path for further expansion.
= 0.4615
= 0.6
