AI - UNIT-2 Descriptive Questions

UNIT-2: SHORT ANSWER - QUESTIONS (2M)

Q. no	Question Description
1	Differentiate between Informed Search and Uninformed Search with suitable example.
2	Discuss search problems and solutions with an example.
3	Define the Evaluation functions.
4	Describe the heuristic search and its importance in AI problem-solving.
5	Define State space search
6	Write the importance of AND–OR arc in problem formulation and list differences between A* and AO*.
7	What is Local Maxima in Hill Climbling.
8	What is meant by Problem Reduction.
9	What is Plateau and Rigid.
10	Describe Best First Search. How it is differ from Breadth First Search.
11	What is meant by depth and branching factor.
12	Explain Uniform cost search.
13	What is meant by Local Search in AI.

UNIT-2: LONG ANSWER - QUESTIONS (5M).

Q. no	Question Description
1	Describe the difference between BFS and DFS with suitable examples.
2	Develop A* algorithm of AI Application.
3	Describe the Breadth First Search algorithm along with an example.
4	Explain the Depth First Search algorithm along with an example.
5	Apply the AO* search algorithm and solve the AI application problem along with an example.
6	Describe the MINIMAX search algorithm along with an example.
7	Describe the ALPHA-BETA Pruning search algorithm along with an example.
8	Define adversarial search and describe the mini-max algorithm with an example.
9	Explain the concept of problem reduction in AI search.
10	Define evaluation functions and their importance in game-playing.
11	Illustrate the heuristic Hill Climbing algorithm with an example.
12	Explain Uniform Cost search algorithm with a suitable example.
13	Implement the Depth-Limited Search algorithm for a suitable problem with an example.
14	Apply Greedy Best First Search for the following map and find the optimal path to reach goal “Bucharest”.
15	Find the optimal path to reach goal state ‘G’ from start state using A search.*
16	Discuss the types of Hill Climbling algorithm and mention their drawbacks.
17	Demonstrate the application of the Generate-and-Search approach in solving a local search problem with an example.
18	Describe the representation of Games as a Search problem and construct the game tree representation for any game.
19	Demonstrate the differences between A* and AO* Search algorithms with a suitable example.