CS6659 AI 2marks 16marks, Artificial Intelligence Question Bank, AI Short Answers – IT 6th SEM Anna University


Anna University Regulation 2013 Information Technology (IT) CS6659 AI 2marks & 16marks for all 5 units are provided below. Download link for IT 6th SEM CS6659 Artificial Intelligence Short answers, Question Bank are listed down for students to make perfect utilization and score maximum marks with our study materials.

1. What is the use of QUEUING_FN?
QUEUING_FN inserts asset of elements into the queue. Different varieties of queuing fn produce different varieties of the search algorithm.
2. Mention the criteria for the evaluation of search strategy.
There are 4 criteria: Completeness, time complexity, space complexity, optimality.
3. Differentiate blind search& heuristic search.
Blind search has no information about the no. of steps or the path cost from the current state to the goal, they can distinguish a goal state from nongoal state. Heuristic search-knowledge given. Problem specification solution is best.
4. List the various search strategies.
a. BFS b. Uniform cost search
c. DFS d. Depth limited search
e. Iterative deepening search f. Bidirectional search
5. List the various informed search strategy.
Best first search –greedy search ,A* search Memory bounded search-Iterative deepening A*search -simplified memory bounded A*search Iterative improvement search –hill climbing -simulated annealing
6. Differentiate BFS & DFS.
BFS means breath wise search. Space complexity is more. Do not give optimal solution Queuing fn is same as that of queue operator DFS means depth wise search.Space complexity is less Gives optimal solution Queuing fn is some what different from queue operator.
7. Whether uniform cost search is optimal?
Uniform cost search is optimal & it chooses the best solution depending on the path cost.
8. Write the time & space complexity associated with depth limited search.
Time complexity =O (bd) , b-branching factor, d-depth of tree Space complexity=o (bl)
9. Define iterative deepening search.
Iterative deepening is a strategy that sidesteps the issue of choosing the best depth limit by trying all possible depth limits: first depth 0, then depth 1,then depth 2& so on.
10. Define CSP
A constraint satisfaction problem is a special kind of problem satisfies some additional structural properties beyond the basic requirements for problem in general. In a CSP; the states are defined by the values of a set of variables and the goal test specifies a set of constraint that the value must obey.

11. Give the drawback of DFS.
The drawback of DFS is that it can get stuck going down the wrong path. Many problems have very deep or even infinite search tree. So DFS will never be able to recover from an unlucky choice at one of the nodes near the top of the tree. So DFS should be avoided for search trees with large or infinite maximum depths.
12. What is called as bidirectional search?
The idea behind bidirectional search is to simultaneously search both forward from the initial state & backward from the goal & stop when the two searches meet in the middle.
13. Explain depth limited search.
Depth limited avoids the pitfalls of DFS by imposing a cut off of the maximum depth of a path. This cutoff can be implemented by special depth limited search algorithm or by using the general search algorithm with operators that keep track of the depth.
CS6659 AI Unit 1 2marks & 16marks – Download Here
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