1. What is the full form of “AI” ?
(a) Artificially Intelligent
(b) Artificial Intelligence
(c) Artificially Intelligence
(d) Advanced Intelligence
2. Artificial Intelligence is about ________________.
(a) Putting your intelligence in machine
(b) Programming on machine with your own intelligence
(c) Making a Machine intelligent
(d) Playing a Game on computer
3. What is Artificial Intelligence?
(a) Artificial Intelligence is a field that aims to make humans more intelligent
(b) Artificial Intelligence is a field that aims to improve the security
(c) Artificial Intelligence is a field that aims to develop intelligent machines
(d) Artificial Intelligence is a field that aims to mine the data
4. What is the primary goal of Artificial Intelligence (AI)?
(a) To develop machines that can think and act like humans
(b) To automate routine tasks and processes
(c) To simulate human intelligence into machines
(d) To improve computational efficiency and speed
5. What is the primary goal of Artificial Intelligence?
(a) To create systems that require human input to operate
(b) To develop systems that simulate human intelligence processes
(c) To replace all jobs currently performed by humans
(d) To enhance computer processing speeds
6. Which of the following is not a goal of AI?
(a) Thinking humanly
(b) Adapting to the environment and situations
(c) To rule over humans
(d) Real Life Problem Solving
7. What is the main aim of Artificial Intelligence?
(a) To solve real-world problems
(b) To explain various sorts of intelligence
(c) To solve artificial problems
(d) To obtain information about scientific causes
8. Who is known as the inventor of Artificial Intelligence?
(a) Charles Babbage
(b) Andrew Ng
(c) John McCarthy
(d) Alan Turing
Explanation: John McCarthy was a pioneer in artificial intelligence researcher who spend years teaching computers to grasp the concepts that are intuitive to human beings.
9. Who is known as the “Father of AI”?
(a) Fisher Ada
(b) Alan Turing
(c) John McCarthy
(d) Allen Newell
10. In which year was the term “Artificial Intelligence” first coined?
(a) 1945
(b) 1956
(c) 1960
(d) 1972
11. 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
12. 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
13. The conference that launched the AI revolution in 1956 was held at?
(a) Dartmouth
(b) Harvard
(c) New York
(d) Stanford
14. The “Father of Artificial Intelligence” is:
(a) Charles Babbage
(b) John McCarthy
(c) Allen Newell
(d) Alan Turing
15. What is meant by Artificial Intelligence?
(a) Artificial intelligence is defined as a field aiming to make humans more intelligent.
(b) Artificial intelligence is defined as a field aiming to improve security.
(c) Artificial intelligence is defined as a field aiming to mine the data.
(d) Artificial intelligence is defined as a field aiming to develop intelligent machines.
16. Artificial Intelligence is _______
(a) the embodiment of human intellectual capabilities within a computer.
(b) a set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans.
(c) the study of mental faculties through the use of mental models implemented on a computer.
(d) All of the above
17. Artificial Intelligence is associated with computers of which generation?
(a) Second
(b) First
(c) Fifth
(d) Third
18. Which of the following is the branch of Artificial Intelligence?
(a) Machine Learning
(b) Cyber forensics
(c) Full-Stack Developer
(d) Network Design
19. Which of the following is an application of Artificial Intelligence?
(a) It helps to exploit vulnerabilities to secure the firm
(b) Language understanding and problem-solving (Text analytics and NLP)
(c) Easy to create a website
(d) It helps to deploy applications on the cloud
20. Which of the following is not an application of artificial intelligence?
(a) Face recognition system
(b) Chatbots
(c) LIDAR
(d) DBMS
21. ___________ is not an application of Artificial Intelligence.
(a) Database Management System
(b) Digital Assistants
(c) Natural Language Processing
(d) Computer Vision
22. The application/applications of Artificial Intelligence is/are
(a) Expert Systems
(b) Gaming
(c) Vision Systems
(d) All of the above
23. Which of the following is NOT a type of AI as defined by capabilities?
(a) Narrow AI
(b) General AI
(c) Supervised AI
(d) Super AI
24. What is the difference between Narrow AI and General AI?
(a) Narrow AI performs specific tasks
(b) General AI performs specific tasks
(c) Narrow AI has the capability to perform any intellectual task
(d) General AI is currently in widespread use
25. Weak AI is ________________
(a) the embodiment of human intellectual capabilities within a computer.
(b) a set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans.
(c) the study of mental faculties through the use of mental models implemented on a computer.
(d) All of the above
26. Strong AI is ________________
(a) the embodiment of human intellectual capabilities within a computer.
(b) a set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans.
(c) the study of mental faculties through the use of mental models implemented on a computer.
(d) All of the above
27. Which of the following is an example of General AI?
(a) IBM’s Watson
(b) Siri
(c) Google’s AlphaGo
(d) None of the above
28. What are the different types of Artificial Intelligence approaches?
(a) Strong Approach
(b) Weak Approach
(c) Applied Approach
(d) All of the above
29. What is the main task of a problem-solving agent?
(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
30. What is state space in AI?
(a) Collection of all the problem states
(b) A specific problem state out of all the problem state
(c) Both a and b
(d) None of the above
31. Which of the following definitions correctly defines the State Space in an AI System?
(a) A state space can be defined as the collection of all the problem states
(b) A state space is a state which exists in an environment which is in outer space
(c) A state space is the total space accessible to the agent in the state
(d) All of the above
32. The correct ways to solve a problem of state-space search are?
(a) Forward from the initial state
(b) Backward from the goal state
(c) Both A and B
(d) None of the above
33. How many ways are available to solve the state-space search?
(a) 1
(b) 2
(c) 3
(d) 4
Explanation: There are two ways available to solve the state-space search. They are forward from the initial state and backward from the goal.
34. Which is the most straightforward approach for planning algorithm?
(a) Best-first search
(b) State-space search
(c) Depth-first search
(d) Hill-climbing search
Explanation: The straightforward approach for planning algorithm is state space search because it takes into account of everything for finding a solution.
35. What is the other name for forward state-space search?
(a) Progression planning
(b) Regression planning
(c) Test planning
(d) None of the mentioned
36. 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
37. A problem in a search space is defined by one of these states.
(a) Initial state
(b) Last state
(c) Intermediate state
(d) All of the mentioned
38. What is the first step in the problem-solving process in AI?
(a) Define the problem
(b) Develop an algorithm
(c) Test the solution
(d) Implement the solution
39. How many parts does a problem consists of?
(a) 1
(b) 2
(c) 3
(d) 4
Explanation: The four parts of the problem are initial state, set of actions, goal test and path cost.
40. How many states are available in state-space search?
(a) 1
(b) 2
(c) 3
(d) 4
Explanation: There are four states available in state-space search. They are initial state, actions, goal test and step cost.
41. What is the main advantage of backward state-space search?
(a) Cost
(b) Actions
(c) Relevant actions
(d) All of the mentioned
Explanation: The main advantage of backward search will allow us to consider only relevant actions.
42. What are taken into account of state-space search?
(a) Postconditions
(b) Preconditions
(c) Effects
(d) Both Preconditions & Effects
43. What is the other name of the backward state-space search?
(a) Regression planning
(b) Progression planning
(c) State planning
(d) Test planning
44. Which of the following is a common strategy used in AI problem-solving?
(a) Brute force search
(b) Binary search
(c) Merge sort
(d) Quick sort
45. Which of the following is a disadvantage of using brute force search in AI?
(a) It is not guaranteed to find a solution
(b) It requires domain-specific knowledge
(c) It is computationally expensive
(d) It only works for small datasets
Explanation: Brute force search is often computationally expensive because it involves trying all possible solutions, which can be time-consuming and resource-intensive.
46. Your AI solution is taking too long to find a solution using brute force. What is a possible solution?
(a) Increase the dataset size
(b) Switch to a heuristic-based search
(c) Add more processing power
(d) Decrease the dataset size
Explanation: Switching to a heuristic-based search can significantly reduce the time taken to find a solution by guiding the search process more efficiently.
47. Which of the following is an example of a problem that can be solved using AI?
(a) Multiplying two numbers
(b) Solving a maze
(c) Calculating the square root
(d) Adding two integers
48. What is the primary purpose of using a search algorithm in AI problem-solving?
(a) To store data efficiently
(b) To navigate through a solution space
(c) To sort data
(d) To implement AI models
Explanation: Search algorithms help AI systems navigate through a solution space to find the best or most optimal solution to a problem.
49. What is the main purpose of search algorithms in AI?
(a) To find the best sorting method
(b) To explore possible solutions
(c) To enhance data storage
(d) To simplify coding
Explanation: Search algorithms in AI are primarily used to explore possible solutions in a defined problem space.
50. In state-space, the set of actions for a given problem is expressed by the ____________ .
(a) Intermediate states
(b) Initial state
(c) Successor function that takes current action and returns next state
(d) None of the above
51. Which AI technique involves breaking down a problem into smaller sub-problems?
(a) Divide and conquer
(b) Greedy algorithm
(c) Heuristic search
(d) Depth-first search
52. The process of removing detail from a given state representation is called ______________
(a) Extraction
(b) Abstraction
(c) Information Retrieval
(d) Mining of data
53. A problem-solving approach works well for ______________
(a) 8-Puzzle problem
(b) 8-queen problem
(c) Finding a optimal path from a given source to a destination
(d) Mars Hover (Robot Navigation)
54. In which search problem, to find the shortest path, each city must be visited once only?
(a) Map coloring Problem
(b) Depth-first search traversal on a given map represented as a graph
(c) Finding the shortest path between a source and a destination
(d) Travelling Salesman problem
55. 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
56. What is the major component /components for measuring the performance of problem solving?
(a) Completeness
(b) Optimality
(c) Time and Space complexity
(d) All of the mentioned
57. Which search strategy is also called as blind search?
(a) Uninformed search
(b) Informed search
(c) Simple reflex search
(d) All of the mentioned
58. What is the general term of Blind searching?
(a) Informed Search
(b) Uninformed Search
(c) Informed & Unformed Search
(d) Heuristic Search
59. Select the most appropriate situation for that a blind search can be used.
(a) Real-life situation
(b) Small Search Space
(c) Complex game
(d) All of the above
60. Which of the following is an example of an uninformed search algorithm?
(a) A* search
(b) Breadth-first search
(c) Hill climbing
(d) Genetic algorithm
Explanation: Breadth-first search is an uninformed search algorithm, meaning it explores the search space without using domain-specific knowledge.
61. In which of the following situations might a blind search be acceptable?
(a) real-life situation
(b) complex game
(c) small search space
(d) all of the mentioned
62. Blind Search can be used for which of the following situations?
(a) Advanced Game Theory
(b) Real-life Simulation
(c) Small Search Space
(d) None of the above
63. 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
64. 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
65. In BFS, which data structure is typically used to store the frontier ?
(a) Stack
(b) Queue
(c) Heap
(d) Hash table
66. 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
67. 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
68. 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
69. 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
70. Which search algorithm traverses one side of the tree before the other?
(a) The Breadth First Search (BFS)
(b) The Depth First Search (DFS)
(c) The A* search
(d) None of the above
71. Which of the following search method takes less memory space?
(a) Depth-First Search
(b) Breadth-First search
(c) Optimal search
(d) Linear Search
72. 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
Explanation: Depth-first search always expands the deepest/leaf node in the current fringe of the search tree.
73. What role does backtracking play in AI problem-solving?
(a) It avoids revisiting already explored paths
(b) It guarantees finding the optimal solution
(c) It simplifies the problem
(d) It is used to store solutions
Explanation: Backtracking is a technique that avoids revisiting paths that have already been explored, helping to efficiently find solutions.
74. 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
Explanation: Breadth-first search always expands the shallowest node in the current fringe of the search tree. Traversal is performed level wise.
75. Which data structure conveniently used to implement BFS?
(a) Stacks
(b) Queues
(c) Priority Queues
(d) All of the mentioned
76. Which data structure conveniently used to implement DFS?
(a) Stacks
(b) Queues
(c) Priority Queues
(d) All of the mentioned
77. LIFO is __________ where as FIFO is ___________
(a) Stack, Queue
(b) Queue, Stack
(c) Priority Queue, Stack
(d) Stack. Priority Queue
78. What is the key difference between depth-first search (DFS) and breadth-first search (BFS)?
(a) DFS uses a queue, BFS uses a stack
(b) DFS uses a stack, BFS uses a queue
(c) DFS is informed, BFS is uninformed
(d) DFS is optimal, BFS is not
79. Uniform-cost search expands the node n with the _____________
(a) Lowest path cost
(b) Heuristic cost
(c) Highest path cost
(d) Average path cost
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.
80. What is the other name of informed search strategy?
(a) Simple search
(b) Heuristic search
(c) Online search
(d) None of the mentioned
81. 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
82. What is the primary advantage of using informed search algorithms over uninformed ones?
(a) They guarantee finding a solution
(b) They use heuristics to guide the search
(c) They are faster
(d) They require less memory
Explanation: Informed search algorithms use heuristics to guide the search process, making them generally more efficient than uninformed algorithms.
83. Which of the following are informed search method?
(a) Memory Bound Heuristic Search
(b) A * Search
(c) Best First Search
(d) All of the above
84. Which of the following are heuristic search algorithms?
(a) Best First Search Algorithm
(b) A* Search Algorithm
(c) Both a and b
(d) None of the above
85. Which of the following searches are Heuristic Searches?
(a) Random Search
(b) Depth First Search
(c) Breadth-First Search
(d) Best First Search
86. Which property differentiates Heuristic Search from other searches?
(a) It provides a solution in a reasonable time frame
(b) It provides a reasonably accurate direction to a goal
(c) It considers both actual and approximate costs
(d) All of the above
87. Strategies that know whether one non-goal state is “more promising” than another are called _________________.
(a) Informed & Unformed Search
(b) Unformed Search
(c) Heuristic & Unformed Search
(d) Informed & Heuristic Search
88. _____________ is the informed search method.
(a) Memory Bound Heuristic Search
(b) A * Search
(c) Best First Search
(d) All of the above
89. The search strategy that uses a problem specific knowledge is known as __________________
(a) Informed Search
(b) Best First Search
(c) Heuristic Search
(d) All of the mentioned
90. 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 the other is
(d) All of the mentioned
Explanation: In a heuristic approach, we discover certain idea and use heuristic functions to search for a goal and predicates to compare nodes.
91. In informed search techniques, what type of information guides the search process?
(a) Heuristic information
(b) Random exploration
(c) Uninformed criteria
(d) Depth-first traversal
92. In AI, what does the term “heuristic” refer to?
(a) A guaranteed solution
(b) A shortcut to find a good solution
(c) An exact algorithm
(d) A random solution
93. 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
Explanation: The lowest expansion node is selected because the evaluation measures distance to the goal.
94. Which search uses only the linear space for searching?
(a) Best-first search
(b) Recursive best-first search
(c) Depth-first search
(d) None of the mentioned
Explanation: Recursive best-first search will mimic the operation of standard best-first search, but using only the linear space.
95. 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
96. Best-First search can be implemented using the following data structure.
(a) Queue
(b) Stack
(c) Priority Queue
(d) Circular Queue
97. 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)
98. Which statement is valid for the Heuristic function?
(a) The heuristic function is used to solve mathematical problems.
(b) The heuristic function takes parameters of type string and returns an integer value.
(c) The heuristic function does not have any return type.
(d) The heuristic function calculates the cost of an optimal path between the pair of states.
99. 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
100. Greedy search strategy chooses the node for expansion in __________________
(a) Shallowest
(b) Deepest
(c) The one closest to the goal node
(d) Minimum heuristic cost
Explanation: Because of using greedy best-first search, It will quickly lead to the solution of the problem.
101. Which of the following is NOT a characteristic of the greedy best-first search algorithm?
(a) It is optimal
(b) It uses a heuristic function
(c) It is not complete in some cases
(d) It can be faster than other algorithms
Explanation: Greedy best-first search is not guaranteed to be optimal as it prioritizes nodes based on a heuristic that may not lead to the best overall solution.
102. What is the evaluation function in greedy approach?
(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
103. A* algorithm is based on ________________
(a) Breadth-First-Search
(b) Depth-First –Search
(c) Best-First-Search
(d) Hill climbing
Explanation: Best-first-search is giving the idea of optimization and quick choose of path, and all these characteristic lies in A* algorithm.
104. In the A* algorithm, what is the function that combines the cost-so-far and the estimated cost-to-go to find the best path?
(a) F(n)=g(n)+h(n)
(b) F(n)=g(n)-h(n)
(c) F(n)=g(n)*h(n)
(d) F(n)=g(n)/h(n)
105. 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
106. In which scenario is using A* search algorithm preferable?
(a) When the path cost is uniform
(b) When the heuristic is not admissible
(c) When the search space is small
(d) When the goal is to find the shortest path efficiently
107. 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
108. 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
109. What is the evaluation function in A* approach?
(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
110. Which of the following is not an uninformed search algorithm in AI?
(a) BFS
(b) DFS
(c) A*
(d) Uniform Cost Search
111. Which of the following algorithms uses a priority queue to manage the exploration of nodes?
(a) Depth-first search
(b) Breadth-first search
(c) A* search
(d) Hill climbing
112. What role does the heuristic function play in the A* search algorithm?
(a) It ensures optimality
(b) It estimates the cost to reach the goal
(c) It guarantees completeness
(d) It defines the search space
Explanation: The heuristic function in the A* search algorithm estimates the cost to reach the goal from a given node, guiding the search process more efficiently.
113. Your search algorithm is not finding the optimal solution. What could be the issue?
(a) The algorithm is not greedy enough
(b) The heuristic function is not admissible
(c) The dataset is too small
(d) The algorithm is too simple
Explanation: If the heuristic function is not admissible, it may overestimate the cost of reaching the goal, leading the search algorithm to miss the optimal solution.
114. An algorithm A is admissible if ______________
(a) It is not guaranteed to return an optimal solution when one exists
(b) It is guaranteed to return an optimal solution when one exists
(c) It returns more solutions, but not an optimal one
(d) It guarantees to return more optimal solutions
115. Your A* search algorithm is not finding the optimal solution. What could be the issue?
(a) The heuristic is overestimating
(b) The priority queue is too small
(c) The graph is weighted
(d) The nodes are not sorted
Explanation: If the heuristic function overestimates the cost, A* search may fail to find the optimal solution as it relies on accurate cost estimation.
116. Your greedy best-first search algorithm is not finding a valid solution. What might be the cause?
(a) The heuristic function is not admissible
(b) The search space is too large
(c) The graph is unweighted
(d) The algorithm is too simple
Explanation: If the heuristic function is not admissible, it might lead the search away from the valid path, causing the algorithm to fail in finding a solution.
117. 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
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 neighbours of that state.
118. 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
119. _______________ 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
120. When will Hill-Climbing algorithm terminate?
(a) Stopping criterion met
(b) Global Min/Max is achieved
(c) No neighbour has higher value
(d) All of the mentioned
121. What are the main cons of hill-climbing search?
(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
122. 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
123. Hill-Climbing approach stuck for which of the following reasons?
(a) Local maxima
(b) Ridges
(c) Plateau
(d) All of the mentioned
124. Which of the following algorithm is online search algorithm?
(a) Breadth-first search algorithm
(b) Depth-first search algorithm
(c) Hill-climbing search algorithm
(d) None of the mentioned
125. 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
126. 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
127. The initial state and the legal moves for each side define the ______________ for the game.
(a) Search Tree
(b) Game Tree
(c) State Space Search
(d) Forest
128. 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
Explanation: Because we need to cut the search off at some point and apply an evaluation function that gives an estimate of the utility of the state.
129. Which Algorithm is Used for Victory/Defeat Decision-Making in Game Trees?
(a) BFS
(b) Heuristic search
(c) Min/max algorithm
(d) DFS
130. Which of the following algorithm is used in Game tree to make Win/Lose decision?
(a) Heuristic Search Algorithm
(b) DFS/BFS algorithm
(c) Greedy Search Algorithm
(d) Min-Max algorithm
131. Decisions of Victory/Defeat are made in Game trees using which algorithm?
(a) DFS
(b) BFS
(c) Heuristic Search
(d) Min-Max Algorithm
132. 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
133. Which search is similar to minimax search?
(a) Hill-climbing search
(b) Depth-first search
(c) Breadth-first search
(d) All of the mentioned
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.
134. The search algorithm which is similar to the minimax search, but removes the branches that don’t affect the final output is known as ___________________ .
(a) Depth-first search
(b) Breadth-first search
(c) Alpha-beta pruning
(d) None of the above
135. 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
136, 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
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.
137. How the effectiveness of the alpha-beta pruning gets increased?
(a) Depends on the nodes
(b) Depends on the order in which they are executed
(c) All of the mentioned
(d) None of the mentioned
138. 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
Explanation: Alpha-beta search updates the value of alpha and beta as it gets along and prunes the remaining branches at node.
139. The maximum depth to which the alpha-beta pruning can be applied.
(a) Eight states
(b) Six states
(c) Ten states
(d) Any depth
140. To which depth does the alpha-beta pruning can be applied?
(a) 10 states
(b) 8 States
(c) 6 States
(d) Any depth