Approaches to AI: Turing Test, rational agents, state-space representation, heuristic search, game playing and alpha–beta pruning. - One Line Questions

1. In Minimax, if a MIN node has children with values {3, 5, 2}, what value will the MIN node choose? — 2
2. What is the difference between an 'admissible' and a 'consistent' heuristic? — A consistent heuristic is always admissible, but an admissible heuristic is not always consistent.
3. Which of the following scenarios would most benefit from Alpha-Beta Pruning? — A complex game like Chess or Go with a large branching factor.
4. In a state-space search, what is a 'node' typically used to represent? — A configuration or situation of the problem.
5. In the context of state-space search, an 'action' typically represents: — A transition between states.
6. What is a 'terminal state' in the context of state-space search and game playing? — A state from which no further actions can be taken.
7. In the context of Artificial Intelligence, what is a 'rational agent' defined as? — An agent that acts so as to achieve the best outcome or the best expected outcome.
8. Which of the following best describes a 'reflex agent'? — An agent that acts based solely on the current percept, without considering history.
9. In state-space search, the 'path cost' function, g(n), typically represents: — The actual cost of the path from the initial state to node n.
10. In a two-player zero-sum game, the Minimax algorithm assumes: — One player tries to maximize their score, and the other tries to minimize it.
11. Which type of search algorithm explores the most promising nodes first based on some evaluation function? — Heuristic Search
12. The Turing Test is primarily a test of: — Linguistic intelligence
13. Which search algorithm is guaranteed to find the optimal solution if the heuristic is admissible? — A* Search
14. Which search algorithm explores nodes in increasing order of path cost, guaranteeing optimality? — Uniform Cost Search
15. Which search algorithm guarantees finding the shortest path in terms of the number of edges (or steps) in an unweighted graph? — Breadth-First Search (BFS)
16. A heuristic function h(n) = 0 for all n is equivalent to which search algorithm? — Breadth-First Search
17. An 'admissible' heuristic function h(n) in AI search guarantees that: — h(n) is always less than or equal to the true cost from node n to the goal.
18. What is the term for a game tree search technique that aims to improve upon Minimax by eliminating redundant exploration? — Alpha-Beta Pruning
19. Which of the following is an example of a problem that can be effectively solved using state-space representation and search algorithms? — Solving the Tower of Hanoi puzzle
20. What is the primary drawback of Breadth-First Search (BFS) for very large state spaces? — It requires a large amount of memory to store the frontier.
21. What is the primary advantage of Alpha-Beta Pruning over a standard Minimax search? — It explores fewer nodes in the game tree, making the search more efficient.
22. What is the main advantage of using a heuristic function in AI search? — It significantly reduces the search space and speeds up the search process.
23. Which of the following is a characteristic of the 'state' in a state-space search? — It represents a unique configuration or situation in the problem.
24. Which of the following is a limitation of the Turing Test? — It only tests linguistic intelligence, not other forms.
25. A heuristic function that overestimates the cost to reach the goal is problematic because: — It may cause the search algorithm to miss the optimal solution.
26. Who proposed the Turing Test as a measure of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human? — Alan Turing
27. What does 'state-space representation' in AI typically involve? — Representing a problem as a graph where nodes are states and edges are actions.
28. A state-space representation where the number of states is finite but potentially very large is characteristic of problems like: — Robotics path planning
29. An agent that has a 'model of the world' and uses it to predict the effect of actions is known as a: — Model-based agent
30. An agent that perceives its environment through sensors and acts upon that environment through actuators is known as a: — Intelligent agent
31. The core idea of the Turing Test is to assess if a machine can exhibit intelligence by: — Engaging in natural language conversation indistinguishably from a human.
32. A 'percept' in the context of intelligent agents refers to: — The sequence of inputs received from the environment.
33. A 'fully observable' environment in the context of rational agents means: — The agent's percept sequence is sufficient to identify the best action.
34. The 'imitation game' is another name for which AI test? — The Turing Test
35. The 'frame problem' in AI, particularly relevant to state-space representation, refers to: — The challenge of efficiently determining which facts change and which remain the same when an action is performed.
36. An agent that operates in an environment that is 'stochastic' means: — The outcome of actions is uncertain and probabilistic.
37. The concept of 'planning' in AI relates to: — Finding a sequence of actions to achieve a goal.
38. According to the Turing Test, if a human interrogator cannot reliably distinguish between a human and a machine after a series of questions, what can be concluded? — The machine has passed the test and demonstrated human-like intelligence.
39. Consider the Turing Test. If a machine can fool an interrogator into believing it is human, it implies: — The machine has achieved human-level intelligence in conversational ability.
40. Which of the following best describes the 'state' in a state-space representation for a navigation problem? — The agent's current location and orientation.
41. Which of these is a common heuristic for the 8-puzzle problem? — The Manhattan distance of the tiles from their goal positions.
42. In Alpha-Beta Pruning, if a node at depth 'd' is found to have a move that is worse than a previously explored option at the same level, what happens? — The entire subtree rooted at that node is pruned.
43. Consider the 8-puzzle problem. The 'state' in its state-space representation would typically be: — The current arrangement of the tiles on the board.
44. What is the primary purpose of the 'evaluation function' in game playing AI algorithms like Minimax with Alpha-Beta Pruning? — To assign a numerical score to a board position, estimating its favorability.
45. What is the primary goal of Alpha-Beta Pruning in game playing AI? — To reduce the number of nodes evaluated in a minimax search by eliminating branches that are provably worse than other options.
46. What is the fundamental principle behind the Minimax algorithm in game playing? — To find a move that is best assuming the opponent plays optimally to counter your moves.
47. What is the primary goal of the 'MAX' player in the Minimax algorithm? — To maximize its own score, assuming the MIN player plays optimally to minimize it.
48. The ability of an AI system to learn and adapt its behavior based on new information is a key aspect of which AI approach? — Rational Agents
49. In Alpha-Beta Pruning, what is the condition under which a MAX node's value is determined? — When any of its children has a value greater than or equal to the current MIN node's value.
50. The concept of 'strong AI' versus 'weak AI' is related to the interpretation of success in which test? — Turing Test
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