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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) Both a & c
2188In 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
4952In 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
2139A* 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
2285What is the other name of informed search strategy? a) Simple search b) Heuristic search c) Online search d) None of the mentioned
5226What 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)
1560Which 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
3041Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned
3981Which 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
4852In 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) Only a and b
2771Though 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) No optimum solution
2205A 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
2016_______________ 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
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Define the nlp terminology?
What is graph in tensorflow ?
Give an example of a data set that has a non-gaussian distribution?
Hill-Climbing approach stuck for the following reasons a) Local maxima b) Ridges c) Plateaux d) All of above
Can you define power analysis?
How can AI improve hospital resource management?
What is skewed distribution & uniform distribution?
What is the definition of the unit test?
A* algorithm is based on which search method?
What do you understand by Linear Regression in R?
Explain types of artificial intelligence?
What are some potential applications of Edge AI in smart homes and cities for improved automation?
Explain the different types of classifiers?
How many types of activation function are available?
How does natural language processing (NLP) enhance educational tools?
