CSC434-AI&ML
47. A problem in a search space is defined by one of these state. a) Initial state b) Last state c) Intermediate state d) All of the above
Answer: a Explanation: A problem has four components initial state, goal test, set of actions, path cost.
43. A* is optimal if h(n) is an admissible heuristic-that is, provided that h(n) never underestimates the cost to reach the goal. a) True b) False
Answer: a Explanation: A* is optimal if h(n) is an admissible heuristic-that is, provided that h(n) never overestimates the cost to reach the goal. Refer both the example from the book for better understanding of the algorithms.
35. Best-First search is a type of informed search, which uses ________________ to choose the best next node for expansion. a) Evaluation function returning lowest evaluation b) Evaluation function returning highest evaluation c) Evaluation function returning lowest & highest evaluation d) None of them is applicable
Answer: a Explanation: Best-first search is an instance of the general TREE-SEARCH or GRAPH-SEARCH algorithm in which a node is selected for expansion based on an evaluation function, f (n) . Traditionally, the node with the lowest evaluation is selected for expansion, because the evaluation measures distance to the goal.
69. Breadth-first search always expands the ______ node in the current fringe of the search tree. a) Shallowest b) Child node c) Deepest d) Minimum cost
Answer: a Explanation: Breadth-first search always expands the shallowest node in the current fringe of the search tree. Traversal is performed level wise.
52. Which search method takes less memory? a) Depth-First Search b) Breadth-First search c) Linear Search d) Optimal search
Answer: a Explanation: Depth-First Search takes less memory since only the nodes on the current path are stored, but in Breadth First Search, all of the tree that has generated must be stored.
71. LIFO is ______ where as FIFO is ________ a) Stack, Queue b) Queue, Stack c) Priority Queue, Stack d) Stack. Priority Queue
Answer: a Explanation: LIFO is last in first out - Stack. FIFO is first in first out - Queue.
92. The minimax algorithm computes the minimax decision from the current state. It uses a simple recursive computation of the minimax values of each successor state, directly implementing the defining equations. The recursion proceeds all the way down to the leaves of the tree, and then the minimax values are backed up through the tree as the recursion unwinds. a) True b) False
Answer: a Explanation: Refer definition of minimax algorithm.
23. An omniscient agent knows the actual outcome of its actions and can act accordingly; but omniscience is impossible in reality. Rational Agent always does the right thing; but Rationality is possible in reality. State true or false a) True b) False
Answer: a Explanation: Refer the definition of rational and omniscient agents
78. 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 Explanation: Refer to the definition of variants of hill-climbing search.
93. 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: a Explanation: Same as DFS.
67. uniform-cost search expands the node n with the__________ a) Lowest path cost b) Heuristic cost c) Highest path cost d) Average path cost
Answer: a Explanation: Uniform-cost search expands the node n with the lowest path cost. Note that if all step costs are equal, this is identical to breadth-first search.
27. What is the other name of informed search strategy? a) Simple search b) Heuristic search c) Online search d) None of the mentioned
Answer: b Explanation: A key point of informed search strategy is heuristic function, So it is called as heuristic function.
46. A search algorithm takes _________ as an input and returns ________ as an output. a) Input, output b) Problem, solution c) Solution, problem d) Parameters, sequence of actions
Answer: b Explanation: A search algorithm takes input as a problem and returns a solution to the problem as an output.
61. Blind searching is general term for a) Informed Search b) Uninformed Search c) Informed & Unformed Search d) Heuristic Search
Answer: b Explanation: In case of uninformed search no additional information except the problem definition is given.
70. Optimality of BFS is a) When there is less number of nodes b) When all step costs are equal c) When all step costs are unequal d) None of the mentioned
Answer: b Explanation: It always expands the shallowest unexpanded node.
60. Which search implements stack operation for searching the states? a) Depth-limited search b) Depth-first search c) Breadth-first search d) None of the mentioned
Answer: b Explanation: It implements stack operation because it always expands the deepest node in the current tree.
51. The _______ is a touring problem in which each city must be visited exactly once. The aim is to find the shortest tour. a) Finding shortest path between a source and a destination b) Travelling Salesman problem c) Map coloring problem d) Depth first search traversal on a given map represented as a graph
Answer: b Explanation: Refer the TSP problem.
9. What is the rule of simple reflex agent? a) Simple-action rule b) Condition-action rule c) Simple & Condition-action rule d) None of the mentioned
Answer: b Explanation: Simple reflex agent is based on the present condition and so it is condition action rule.
36. Best-First search can be implemented using the following data structure. a) Queue b) Stack c) Priority Queue d) Circular Queue
Answer: c Explanation: Best-first search can be implemented within our general search framework via a priority queue, a data structure that will maintain the fringe in ascending order of f-values.
34. A* algorithm is based on a) Breadth-First-Search b) Depth-First -Search c) Best-First-Search d) Hill climbing
Answer: c Explanation: Best-first-search is giving the idea of optimization and quick choose of path, and all these characteristic lies in A* algorithm.
86. Which value is assigned to alpha and beta in the alpha-beta pruning? a) Alpha = max b) Beta = min c) Beta = max d) Both Alpha = max & Beta = min
Answer: d Explanation: Alpha and beta are the values of the best choice we have found so far at any choice point along the path for MAX and MIN.
25. What could possibly be the environment of a Satellite Image Analysis System? a) Computers in space and earth b) Image categorization techniques c) Statistical data on image pixel intensity value and histograms d) All of the mentioned
Answer: d Explanation: An environment is something which agent stays in.
22. What is rational at any given time depends on a) The performance measure that defines the criterion of success b) The agent's prior knowledge of the environment c) The actions that the agent can perform d) All of the mentioned
Answer: d Explanation: For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.
31. Which search is complete and optimal when h(n) is consistent? a) Best-first search b) Depth-first search c) Both Best-first & Depth-first search d) A* search
Answer: d Explanation: None.
57. What is the space complexity of Depth-first search? a) O(b) b) O(bl) c) O(m) d) O(bm)
Answer: d Explanation: O(bm) is the space complexity where b is the branching factor and m is the maximum depth of the search tree.
41. What is the space complexity of Greedy search? a) O(b) b) O(bl) c) O(m) d) O(bm)
Answer: d Explanation: O(bm) is the space complexity where b is the branching factor and m is the maximum depth of the search tree. Since this algorithm resembles the DFS.
13. What kind of observing environments are present in artificial intelligence? a) Partial b) Fully c) Learning d) Both Partial & Fully
Answer: d Explanation: Partial and fully observable environments are present in artificial intelligence.
3. Following could be the approaches to Artificial Intelligence a) Strong Artificial Intelligence b) Weak Artificial Intelligence c) Applied Artificial Intelligence d) All of the mentioned
Answer: d Explanation: Strong Artificial Intelligence aims to build machines that can truly reason and solve problems. Weak Artificial Intelligence deals with the creation of some form of computer-based artificial intelligence that cannot truly reason and solve problems, but can act as if it were intelligent. Applied Artificial Intelligence aims to produce commercially viable "smart" systems. In Cognitive Artificial Intelligence approach, a computer is used to test theories about how the human mind works.
24. The Task Environment of an agent consists of a) Sensors b) Actuators c) Performance Measures d) All of the mentioned
Answer: d Explanation: The task environment of an agent is described by four parts performance measures, sensors, actuators and environment, generally known as the PEAS descriptions.
73. 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 Explanation: 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.
48. A solution to a problem is a path from the initial state to a goal state. Solution quality is measured by the path cost function, and an optimal solution has the highest path cost among all solutions. State whether true or false. a) True b) False
Answer: a Explanation: A solution to a problem is a path from the initial state to a goal state. Solution quality is measured by the path cost function, and an optimal solution has the lowest path cost among all solutions.
77. 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 Explanation: Algorithm terminates at local optimum values, hence fails to find optimum solution.
87. Where does the values of alpha-beta search get updated? a) Along the path of search b) Initial state itself c) At the end d) None of the mentioned
Answer: a Explanation: Alpha-beta search updates the value of alpha and beta as it gets along and prunes the remaining branches at node.
1. The performance of an agent can be improved by a) Learning b) Observing c) Perceiving d) None of the mentioned
Answer: a Explanation: An agent can improve by saving the previous states on which it was earlier, hence in future it can learn to respond in the same situation better.
7. Which instruments are used for perceiving and acting upon the environment? a) Sensors and Actuators b) Sensors c) Perceiver d) None of the mentioned
Answer: a Explanation: An agent is anything that can be viewed as perceiving and acting upon the environment through the sensors and actuators.
74. 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 Explanation: An algorithm is complete if it finds a solution if exists and optimal if finds optimal goal (minimum or maximum)
21. Performance Measures are fixed for all agents. State true or false a) True b) False
Answer: a Explanation: As a general rule, it is better to design performance measures according to what one actually wants in the environment, rather than according to how one thinks the agent should behave.
14. What kind of environment is crossword puzzle? a) Static b) Dynamic c) Semi Dynamic d) None of the mentioned
Answer: a Explanation: As the problem in crossword puzzle are posed at beginning itself, So it is static.
64. Which data structure conveniently used to implement DFS? a) Stacks b) Queues c) Priority Queues d) All of the mentioned
Answer: a Explanation: DFS requires node to be expanded the one most recent visited, hence stack is convenient to implement.
40. 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: a Explanation: Greedy best-first search3 tries to expand the node that is closest to the goal, on the grounds that this is likely to lead to a solution quickly. Thus, it evaluates nodes by using just the heuristic function: f (n) = h(n).
37. The name "best-first search" is a venerable but inaccurate one. After all, if we could really expand the best node first, it would not be a search at all; it would be a straight march to the goal. All we can do is choose the node that appears to be best according to the evaluation function. State whether true or false. a) True b) False
Answer: a Explanation: If the evaluation function is exactly accurate, then this will indeed be the best node; in reality, the evaluation function will sometimes be off, and can lead the search astray.
54. Which search strategy is also called as blind search? a) Uninformed search b) Informed search c) Simple reflex search d) All of the mentioned
Answer: a Explanation: In blind search, We can search the states without having any additional information. So uninformed search method is blind search.
26. Categorize Crossword puzzle in Fully Observable / Partially Observable. a) Fully Observable b) partially Observable c) All of the mentioned d) None of the mentioned
Answer: a Explanation: In crossword puzzle an agent knows the complete state of the environment through its sensors.
28. Which search uses the problem specific knowledge beyond the definition of the problem? a) Informed search b) Depth-first search c) Breadth-first search d) Uninformed search
Answer: a Explanation: Informed search can solve the problem beyond the function definition, So does it can find the solution more efficiently.
59. Which search algorithm imposes a fixed depth limit on nodes? a) Depth-limited search b) Depth-first search c) Iterative deepening search d) Bidirectional search
Answer: a Explanation: None.
11. In which agent does the problem generator is present? a) Learning agent b) Observing agent c) Reflex agent d) None of the mentioned
Answer: a Explanation: Problem generator will give the suggestion to improve the output for learning agent.
20. Rational agent is the one who always does the right thing. State true or false a) True b) False
Answer: a Explanation: Rational agent is the one who always does the right thing Right in a sense that it makes the agent the most successful.
81. 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 Explanation: 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.
5. A completely automated chess engine (Learn from previous games) is based on a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach
Answer: a Explanation: Strong Artificial Intelligence aims to build machines that can truly reason and solve problems. These machines must be self-aware and their overall intellectual ability needs to be indistinguishable from that of a human being. Strong Artificial Intelligence maintains that suitably programmed machines are capable of cognitive mental states. advertisement
15. Which is used to provide the feedback to the learning element? a) Critic b) Actuators c) Sensor d) None of the mentioned
Answer: a Explanation: The learning element gets the feedback from the critic which is presented in the environment on how the agent is doing.
83. Which values are independent in minimax search algorithm? a) Pruned leaves x and y b) Every states are dependent c) Root is independent d) None of the mentioned
Answer: a Explanation: The minimax decision are independent of the values of the pruned values x and y because of the root values.
65. The time and space complexity of BFS is (For time and space complexity problems consider b as branching factor and d as depth of the search tree.) a) O(bd+1) and O(bd+1) b) O(b2) and O(d2) c) O(d2) and O(b2) d) O(d2) and O(d2)
Answer: a Explanation: We consider a hypothetical state space where every state has b successors. The root of the search tree generates b nodes at the first level, each of which generates b more nodes, for a total of b2 at the second level. Each of these generates b more nodes, yielding b3 nodes at the third level, and so on. Now suppose that the solution is at depth d. In the worst case, we would expand all but the last node at level d (since the goal itself is not expanded), generating bd+1- b nodes at level d+1.
12. Which is used to improve the agents performance? a) Perceiving b) Learning c) Observing d) None of the mentioned
Answer: b Explanation: An agent can improve its performance by storing its previous actions.
56. When is breadth-first search is optimal? a) When there is less number of nodes b) When all step costs are equal c) When all step costs are unequal d) None of the mentioned
Answer: b Explanation: Because it always expands the shallowest unexpanded node.
55. Which search is implemented with an empty first-in-first-out queue? a) Depth-first search b) Breadth-first search c) Bidirectional search d) None of the mentioned
Answer: b Explanation: Because of FIFO queue, it will assure that the nodes that are visited first will be expanded first.
66. Breadth-first search is not optimal when all step costs are equal, because it always expands the shallowest unexpanded node. State whether true or false. a) True b) False
Answer: b Explanation: Breadth-first search is optimal when all step costs are equal, because it always expands the shallowest unexpanded node. If the solution exists in shallowest node no irrelevant nodes are expanded.
32. 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: b Explanation: Good heuristic can be constructed by relaxing the problem, So the performance of heuristic search can be improved.
63. Which data structure conveniently used to implement BFS? a) Stacks b) Queues c) Priority Queues d) All of the mentioned
Answer: b Explanation: Queue is the most convenient data structure, but memory used to store nodes can be reduced by using circular queues.
75. _______________ 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 Explanation: Refer the definition of Hill-Climbing approach.
29. Which function will select the lowest expansion node at first for evaluation? a) Greedy best-first search b) Best-first search c) Depth-first search d) None of the mentioned
Answer: b Explanation: The lowest expansion node is selected because the evaluation measures distance to the goal.
85. Which search is similar to minimax search? a) Hill-climbing search b) Depth-first search c) Breadth-first search d) All of the mentioned
Answer: b Explanation: The minimax search is depth-first search, So at one time we just have to consider the nodes along a single path in the tree.
49. The process of removing detail from a given state representation is called______ a) Extraction b) Abstraction c) Information Retrieval d) Mining of data
Answer: b Explanation: The process of removing detail from a representation is called abstraction.
2. The action of the Simple reflex agent completely depends upon a) Perception history b) Current perception c) Learning theory d) Utility functions
Answer: b Explanation: These agents select actions based on the current perception, ignoring the rest of the perception history.
58. Which algorithm is used to solve any kind of problem? a) Breadth-first algorithm b) Tree algorithm c) Bidirectional search algorithm d) None of the mentioned
Answer: b Explanation: Tree algorithm is used because specific variants of the algorithm embed different strategies
88. Zero sum games are the one in which there are two agents whose actions must alternate and in which the utility values at the end of the game are always the same. a) True b) False
Answer: b Explanation: Utility values are always same and opposite.
53. Which is the best way to go for Game playing problem? a) Linear approach b) Heuristic approach (Some knowledge is stored) c) Random approach d) An Optimal approach
Answer: b Explanation: We use a Heuristic approach, as it will find out brute force computation, looking at hundreds of thousands of positions. e.g Chess competition between Human and AI based Computer.
10. What are the composition for agents in artificial intelligence? a) Program b) Architecture c) Both Program & Architecture d) None of the mentioned
Answer: c Explanation: An agent program will implement function mapping percepts to actions.
8. What is meant by agent's percept sequence? a) Used to perceive the environment b) Complete history of actuator c) Complete history of perceived things d) None of the mentioned
Answer: c Explanation: An agent's percept sequence is the complete history of everything that the agent has ever perceived.
16. What is Artificial intelligence? a) Putting your intelligence into Computer b) Programming with your own intelligence c) Making a Machine intelligent d) Playing a Game
Answer: c Explanation: Because AI is to make things work automatically through machine without using human effort. Machine will give the result with just giving input from human. That means the system or machine will act as per the requirement.
68. Depth-first search always expands the ______ node in the current fringe of the search tree. a) Shallowest b) Child node c) Deepest d) Minimum cost
Answer: c Explanation: Depth-first search always expands the deepest/leaf node in the current fringe of the search tree.
38. 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: c Explanation: Heuristic is an estimated cost.
72. 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 Explanation: 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.
4. An Artificial Neural Network Is based on a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach
Answer: c Explanation: In Cognitive Artificial Intelligence approach, a computer is used to test theories about how the human mind works-for example, theories about how we recognize faces and other objects, or about how we solve abstract problems.
30. What is the heuristic function of greedy best-first search? a) f(n) != h(n) b) f(n) < h(n) c) f(n) = h(n) d) f(n) > h(n)
Answer: c Explanation: None.
79. 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: c Explanation: None.
39. 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: c Explanation: Sometimes minimum heuristics can be used, sometimes maximum heuristics function can be used. It depends upon the application on which the algorithm is applied.
82. 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: c Explanation: The alpha-beta search computes the same optimal moves as minimax, but eliminates the branches that can't influence the final decision.
42. In A* 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: c Explanation: The most widely-known form of best-first search is called A* search. It evaluates nodes by combining g(n),t he cost to reach the node, and h(n.), the cost to get from the node to the goal: f(n) = g(n) + h(n). Since g(n) gives the path cost from the start node to node n, and h(n) is the estimated cost of the cheapest path from n to the goal.
44. The main task of a problem-solving agent is a) Solve the given problem and reach to goal b) To find out which sequence of action will get it to the goal state c) All of the mentioned d) None of the mentioned
Answer: c Explanation: The problem-solving agents are one of the goal-based agents.
76. 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 Explanation: When no neighbor is having higher value, algorithm terminates fetching local min/max.
89. Zero sum game has to be a ______ game. a) Single player b) Two player c) Multiplayer d) Three player
Answer: c Explanation: Zero sum games could be multiplayer games as long as the condition for zero sum game is satisfied.
18. Artificial Intelligence has its expansion in the following application. (Mark all that apply) a) Planning and Scheduling b) Game Playing c) Diagnosis d) All of the mentioned
Answer: d Explanation: All sectors require intelligence and automation for its working.
84. To which depth does the alpha-beta pruning can be applied? a) 10 states b) 8 States c) 6 States d) Any depth
Answer: d Explanation: Alpha-beta pruning can be applied to trees of any depth and it is possible to prune entire subtree rather than leaves.
19. An 'agent' is anything that, a) Perceives its environment through sensors and acting upon that environment through actuators b) Takes input from the surroundings and uses its intelligence and performs the desired operations c) A embedded program controlling line following robot d) All of the mentioned
Answer: d Explanation: An agent is anything that can be viewed as perceiving and acting upon the environment through the sensors and actuators. Mean it takes input from its environment through sensors, performs operation and gives output through actuators.
17. Which is not the commonly used programming language for AI? a) Python b) Java c) LISP d) PHP
Answer: d Explanation: Because PHP is used as a script language, and not of much use for AI practice. All others are used to generate an artificial program.
45. What is state space? a) The whole problem b) Your Definition to a problem c) Problem you design d) Representing your problem with variable and parameter
Answer: d Explanation: Because state space is mostly concerned with a problem, when you try to solve a problem, we have to design a mathematical structure to the problem, which can only be through variables and parameters. eg. You have given a 4-gallon jug and another 3-gallon jug. Neither has measuring marker on it. You have to fill the jugs with water. How can you get exactly 2 gallons of water in to 4 gallons. Here the state space can defined as set of ordered pairs integers(x,y),such that x=0,1,2,3 or 4 and y=0,1,2 or 3;X represents the number of gallons in 4 gallon jug and y represents quantity of water in the 3-gallon jug.
91. 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: d Explanation: Given a game tree, the optimal strategy can be determined by examining the min/max value of each node, which we write as MINIMAX- VALUE(n). The min/max value of a node is the utility (for MAX) of being in the corresponding state, assuming that both players play optimally from there to the end of the game. Obviously, the min/max value of a terminal state is just its utility. Furthermore, given a choice, MAX will prefer to move to a state of maximum value, whereas MIN prefers a state of minimum value.
6. What among the following is/are the example of the intelligent agent/agents? a) Human b) Robot c) Autonomous Spacecraft d) All of the mentioned
Answer: d Explanation: Humans can be looked upon as agents. They have eyes, ears, skin, taste buds, etc. for sensors; and hands, fingers, legs, mouth for effectors. Robots are agents. Robots may have camera, sonar, infrared, bumper, etc. for sensors. They can have grippers, wheels, lights, speakers, etc. for actuators. Autonomous Spacecraft takes decision on its own based on perceptions.
33. A heuristic is a way of trying a) To discover something or an idea embedded in a program b) To search and measure how far a node in a search tree seems to be from a goal c) To compare two nodes in a search tree to see if one is better than another d) All of the mentioned
Answer: d Explanation: In a heuristic approach, we discover certain idea and use heuristic functions to search for a goal and predicates to compare nodes.
80. Hill-Climbing approach stuck for the following reasons a) Local maxima b) Ridges c) Plateaux d) All of the mentioned
Answer: d Explanation: 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.
62. Which of the following is/are Uninformed Search technique/techniques a) Breadth First Search (BFS) b) Depth First Search (DFS) c) Bidirectional Search d) All of the mentioned
Answer: d Explanation: Several uninformed search techniques includes BFS, DFS, Uniform-cost, Depth-limited, Bidirectional search etc.
90. A game can be formally defined as a kind of search problem with the following components: a) Initial State b) Successor Function c) Terminal Test d) All of the mentioned
Answer: d Explanation: The initial state includes the board position and identifies the player to move. A successor function returns a list of (move, state) pairs, each indicating a legal move and the resulting state. A terminal test determines when the game is over. States where the game has ended are called terminal states. A utility function (also called an objective function or payoff function), which gives a numeric value for the terminal states. In chess, the outcome is a win, lose, or draw, with values +1, -1, or 0.
50. A problem solving approach works well for a) 8-Puzzle problem b) 8-queen problem c) Finding an optimal path from a given source to a destination d) Mars Hover (Robot Navigation) e) All of the mentioned
Answer: e Explanation: Problem-solving approach works well for toy problems and real-world problems.