25 questions · about 30 minutes. Press End Mock any time to see your score and the correct answers.
Directions (Q56–60): A domain has three Boolean variables Toothache, Cavity and Catch, with full joint distribution: cavity ∧ toothache: catch 0.108, ¬catch 0.012; cavity ∧ ¬toothache: catch 0.072, ¬catch 0.008; ¬cavity ∧ toothache: catch 0.016, ¬catch 0.064; ¬cavity ∧ ¬toothache: catch 0.144, ¬catch 0.576.
The probability of a toothache, given evidence of a cavity, P(toothache | cavity) is __________.
Correct answer: B. 0.600
P(toothache | cavity) = P(cavity ∧ toothache)/P(cavity) = 0.12/0.2 = 0.6.
P(cavity ∨ toothache) is __________.
Correct answer: C. 0.280
P(cavity ∨ toothache) = 0.2 + 0.2 − 0.12 = 0.28.
The probability for Cavity, given that either Toothache or Catch is true, P(Cavity | toothache ∨ catch) is _______.
Correct answer: D. 0.4615
P(toothache ∨ catch) = 1 − P(¬toothache ∧ ¬catch) = 1 − (0.008 + 0.576) = 0.416. P(cavity ∧ (toothache ∨ catch)) = 0.108 + 0.012 + 0.072 = 0.192. Ratio = 0.192/0.416 ≈ 0.4615.
The process of removing details from a given state representation is called ______
Correct answer: D. Abstraction
Removing details from a state representation is abstraction.
Which of the following is NOT true in problem solving in artificial intelligence?
Correct answer: D. It works on or implements repetition mechanism
AI problem solving uses heuristics, has implicit solution steps and handles imprecise knowledge. A plain repetition mechanism is a trait of conventional programs.
What kind of clauses are available in conjunctive normal form?
Correct answer: A. Disjunction of literals
CNF is a conjunction of clauses, each clause a disjunction of literals.
Which of the following statements are true? α β β
(A) A sentence entails another sentence if α is true in few worlds where 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.
Correct answer: D. (B) and (D) only
Forward and backward chaining suit Horn knowledge bases (B), and propositional logic cannot scale to unbounded environments (D). Entailment needs β true in every world where α is true (A false), and soundness means deriving only entailed sentences — deriving all of them is completeness (C false).
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 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 minimax algorithm.
(D) Optimal play in games of imperfact information does not require reasoning about the current and future belief states of each player.
Correct answer: C. (B) and (C) only
Alpha-beta's pruning depends heavily on move ordering, and it returns the same move as minimax. Minimax is depth-first, and imperfect-information games require reasoning about belief states.
Match List I with List II. List I: A. Branch-and-bound, B. Steepest-ascent hill climbing, C. Constraint satisfaction, D. Means-end analysis. List II: I. Keeps track of all partial paths that can be candidates for further exploration, II. Detects the difference between the current state and the goal state, III. Discovers problem state(s) that satisfy a set of constraints, IV. Considers all moves from the current state and selects the best move.
Correct answer: A. A-I, B-IV, C-III, D-II
Branch and bound keeps all candidate partial paths; steepest ascent looks at every move and takes the best; constraint satisfaction finds states meeting constraints; means-end analysis reduces the difference between current and goal states.
Match List I with List II. List I: A. Greedy best-first search, B. A*, C. Recursive best-first search, D. SMA*. List II: I. Space complexity is O(d), where d is the depth of the deepest optimal solution, II. Incomplete even if the search space is finite, III. Optimal if the optimal solution is reachable; otherwise returns the best reachable solution, IV. Computation and space complexity are too high.
Correct answer: A. A-II, B-IV, C-I, D-III
Greedy best-first can loop even in finite spaces; A* uses too much time and memory; RBFS needs only linear space; SMA* is optimal if the optimal solution fits in memory.
Given below are two statements: V V If two variables 1 and 2 are used for clustering, then consider the following k k = 3 statements for means clustering with V V
Statement I : If 1 and 2 have correlation of 1 the cluster centroid will be in straight line. V V
Statement II : If 1 and 2 have correlation of 0 the cluster centroid will be in straight line. In the light of the above statements, choose the correct answer from the options given below
Correct answer: C. Statement I is correct but Statement II is false
With correlation 1 all points lie on a line, so every cluster centroid (an average of such points) lies on that line. With correlation 0 the points are spread out and the centroids need not be collinear.
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 nondeterministic environments, agents can apply AND-OR search to generate contingent plans that reach the goal regardless of which outcomes occur during execution. In the light of the above statements, choose the correct answer from the options given below
Correct answer: A. Both Statement I and Statement II are true
A genetic algorithm is a stochastic hill-climbing search over a large population, and AND-OR search builds contingent plans for nondeterministic environments. Both are from Russell & Norvig and correct.
According to Dempster-Shafer theory for uncertainty management, Bel(A) Where denotes Belief of event A.
Correct answer: A. Bel(A) + Bel(¬A) ≤ 1
Unlike probabilities, Dempster–Shafer beliefs need not add up: the mass not committed to A or ¬A stays uncommitted, so Bel(A) + Bel(¬A) ≤ 1.
Note on the official key: the official key says option C. Official/PW key is C (= 1), which is the rule for ordinary probability. In Dempster–Shafer theory belief can leave mass unassigned, so the sum is at most 1.
Consider the game tree given below
□ Here ○ and represent MIN and MAX nodes respectively. The value of the root node of the game tree is:
Correct answer: B. 17
Backing values up the game tree (MIN takes the smaller, MAX the larger at each level) gives 17 at the root, per the official key; the figure's leaf values are only partly legible.
Consider the following models: M1: Mamdani model M
2 : Takagi - Sugeno-Kang model M3: Kosko's additive model (SAM) Which of the following option contains examples of additive rule model? M M
Correct answer: B. Only 2 and 3 M M
Following the official key, the Takagi–Sugeno–Kang model and Kosko's standard additive model (SAM) are additive rule models.
A fuzzy conjunction t(x, y) and disjunction s(x, y) form a pair if t(x, y) = 1 − s(1 − x, 1 − y). If t(x, y) = xy/(x + y − xy), then s(x, y) is
Correct answer: B. (x + y − 2xy)/(1 − xy)
s(x, y) = 1 − t(1 − x, 1 − y). With a = 1 − x and b = 1 − y, t = ab/(a + b − ab) and a + b − ab = 1 − xy, so s = 1 − (1 − x)(1 − y)/(1 − xy) = (x + y − 2xy)/(1 − xy).
Let W_ij represent the weight between node i at layer k and node j at layer (k − 1) of a given multilayer perceptron. The weight updation using the gradient descent method is given by
Correct answer: B. W(t+1) = W(t) − α ∂E/∂W
Gradient descent moves the weight against the error gradient: W(t + 1) = W(t) − α ∂E/∂W, with learning rate 0 ≤ α ≤ 1.
The order of schema ?10?101? and ???0??1 are---- ----------- and --------------respectively.
Correct answer: B. 5,2
Order = number of fixed (non-?) positions. ?10?101? fixes 1, 0, 1, 0, 1 (5); ???0??1 fixes two (2).
Let the population of chromosomes in genetic algorithm is represented in terms of binary number. The strength of fitness of a chromosome x in decimal form, , is given by f(x) Sf(x) = where f(x) = x2 Σf(x) P The population is given by where: P = {(01101, (11000), (01000), (10011)} The strength of fitness of chromosome (11000) is -------------
Correct answer: D. 49.2
x values 13, 24, 8, 19 give x² = 169, 576, 64, 361 (sum 1170). Strength of 11000 = 576/1170 ≈ 49.2%.
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?
Correct answer: D. (a), (b) and (c)
Hill climbing can get stuck on local maxima, plateaus and ridges.
Consider the following learning algorithms :
(a) Logistic repression
(b) Back propogation
(c) Linear repression Which of the following option represents classification algorithms?
Correct answer: A. (a) and (b) only
Logistic regression and backpropagation networks classify; linear regression predicts continuous values.
-mean clustering algorithm has clustered the 1st given 8 observations into 3 clusters after iteration as follows:
C1 : {(3, 3), (5, 5), (7, 7)} C2 : {(0, 6), (6, 0), (3, 0)} C3 : {(8, 8), (4, 4)}
What will be the Manhattan distance for (4, 4) C1 observation from cluster centroid in second iteration? –
Correct answer: A. 2
C1's new centroid is ((3+5+7)/3, (3+5+7)/3) = (5, 5). Manhattan distance from (4, 4) = 1 + 1 = 2.
Consider the game tree given below :
Here and represents MIN and MAX nodes respectively. The value of the root node of the game tree is
Correct answer: B. 7
Backing the leaf values up through the MIN and MAX levels gives 7 at the root, per the figure and the official key.
Match List I with List II. List I: (a) Greedy best-first, (b) Lowest cost-first, (c) A* algorithm. List II: (i) Minimal cost(p) + h(p), (ii) Minimal h(p), (iii) Minimal cost(p).
Correct answer: D. (a)-(ii); (b)-(iii); (c)-(i)
Greedy best-first picks minimal h; lowest-cost-first picks minimal path cost; A* picks minimal cost + h.
The STRIPS representation is
Correct answer: B. an action-centric representation
STRIPS describes the world through actions (preconditions and effects): an action-centric representation.
