Artificial Intelligence B.Tech Question Bank : tits.ac.in

Name of the College : Turbomachinery Institute of Technology &Sciences (TITS)
University : JNTU Hyderabad
Department : Computer Science Engineering
Subject Name : Artificial Intelligence
Degree : B.Tech
Year/Sem : III/II
Website : tits.ac.in
Document Type : Question Bank

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TITS Artificial Intelligence Question Bank

Unit – I

1. Define Artificial Intelligence and discuss about underlying assumptions about Physical Symbol system. (June, 2010)
2. Explain briefly about Water jug problem and explain the state Production rules for Water jug problem.

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3. What is AI? Explain any four approaches to AI (Nov., 2010)
4. Compare a computer and human brain and also explain how human brain process the information (Nov., 2008)
5. Explain the Neuron and a simulated neuron with a diagram and compare (Nov., 2008)
6. what is an agent? Explain the vacuum cleaner world example? (Nov., 2008)
7. Discuss about utility based agents (August, 2008)
8. Explain simple reflex agents
9. What are simple reflex agents? Explain with a diagram (August, 2008)
10. What are model based reflex-agents? Explain with a diagram
11. What is 8-puzzle problem? By giving an example explain a stupid movie in 8-puzzle problem

Unit  – II

Searching : Searching for solutions, uniformed search strategies – Breadth first search, depth first Search. Search with partial information (Heuristic search) Greedy best first search, A* search Game Playing: Adversial search, Games, minimax, algorithm, optimal decisions in multiplayer games, Alpha-Beta pruning, Evaluation functions, cutting of search.
1. Explain various blind search strategies (Nov.,2008)
2. How breadth first search works? What are the features and applications of breadth first search (Nov., 2008)
3. What is a greedy best first search? Explain with example and diagram (Nov., 2008, Aug., 2008)
4. what is iterative deepening depth first search? Explain with an algorithm and diagram (Nov., 2008)
5. Explain in detail about A* algorithm (June, 2010)
6. Discuss in detail about algorithm for constraint satisfaction by taking some problem.
7. What are various blind search procedures and heuristic search strategies? Explain why they are named so, with your own example. (August, 2008)
8. Define a heuristic function and explain the linear combination with an example. (August, 2008)
9. Explain the hill climbing, local maximum and plateau with diagram
10.When would best-first search be worse than simple breadth first search? Explain with an example and diagram. (Aug,, 2008)

Unit  – III

Knowledge Representation & Reasons logical Agents, Knowledge – Based Agents, the Wumpus world, logic, propositional logic,Resolution patterns in propos ional logic, Resolution, Forward & Backward. Chaining.
1. Explain difference between simple hill climbing and steepest ascent hill climbing. (Nov., 2008)
2. Explain difference between best first search and steepest ascent hill climbing (Nov., 2008)
3. Explain simulated annealing algorithm with an example (Nov., 2008)
4. Explain why it is a good heuristic to choose the variable that is most constrained, but the value that is least constraining in aCSP Search (Nov., 2008)
5. Jones, Smith, and Clark hold the jobs of programmer, knowledge engineer, and manager. Jones owes the programmer $10. The manager’s spouse prohibits borrowing money. Smith is not married. Your task is to figure out which person has which job. Solve the problem using propositional logic. (Nov., 2008)
6. Discuss in detail about knowledge based agents (May, 2010)
7. Explain the complexity of propositional inference (May, 2010)
8. What is a Wumpus world? Explain with an example acting and reasoning on the wumpus world. (May-10)
9. Describe a generic knowledge based agent. (Nov., 2008)
10.What are the problems with propositional logic? (Nov., 2008)

Unit – IV

First order logic. Inference in first order logic, propositional Vs. first order inference, unification & lifts forward chaining, Backward chaining, Resolution.
1. Comment on propositional Vs. First-order inference (Nov., 2008)
2. How can resolution be used to show that a sentence is (Nov., 2008)

3. Consider the following sentences: (May, 2010)
i. Jack owns a dog
ii. Every dog owner is an animal lover
iii. No animal lover kills an animal
iv. Either Jack or curiosity killed the cat, who is named tuna.
a. Express the original sentences in the first order logic
b. Convert each sentence to implicative normal form
c. State whether curiosity killed the cat, using resolution with refutation.

4. Explain forward chaining algorithm (August, 2008; May, 2010)
5. Explain backward chaining algorithm (August, 2008; May, 2010)
6. What do you mean by semi decidability, What is semi decidability in first order logic? (May, 2010)
7. Comment on Completeness of first order logic. (May, 2010)
8. What do you mean by conjunctive normal form and implicative normal form? (May, 2010)