Question 41 : A heuristic is a way of trying
1. To discover something or an idea embedded in a program
2. To search and measure how far a node in a search tree seems to be from a goal
3. To compare two nodes in a search tree to see if one is better than another
4. All of the mentioned
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Question 42 : Which search method will expand the node that is closest to the goal?
1. Best-first search
2. Greedy best-first search
3. A* search
4. None of the mentioned
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Question 43 : Which is used to improve the performance of heuristic search?
1. Quality of nodes
2. Quality of heuristic function
3. Simple form of nodes
4. None of the mentioned
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Question 44 : Which search is complete and optimal when h(n) is consistent?
1. Best-first search
2. Depth-first search
3. Both Best-first & Depth-first search
4. A* search
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Question 45 : Which method is used to search better by learning?
1. Best-first search
2. Depth-first search
3. Metalevel state space
4. None of the mentioned
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Question 46 : Which search uses only the linear space for searching?
1. Best-first search
2. Recursive best-first search
3. Depth-first search
4. None of the mentioned
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Question 47 : What is the heuristic function of greedy best-first search?
1. f(n) != h(n)
2. f(n) < h(n)
3. f(n) = h(n)
4. f(n) > h(n)
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Question 48 : Which function will select the lowest expansion node at first for evaluation?
1. Greedy best-first search
2. Best-first search
3. Depth-first search
4. None of the mentioned
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Question 49 : Which search uses the problem specific knowledge beyond the definition of the problem?
1. Informed search
2. Depth-first search
3. Breadth-first search
4. Uninformed search
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Question 50 : How many types of informed search method are in artificial intelligence?
1. 1
2. 2
3. 3
4. 4
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