ARTIFICIAL INTELLIGENCE MAY08 - B.E

T 3184

B.E DEGREE EXAMINATION, APRIL /MAY 2008

SIXTH SEMESTER

CS 1351 –ARTIFICIAL INTELLIGENCE

Part –a 

1. Define artificial intelligence

2. What is the use of heuristic functions

3. How to improve the effectiveness of a search based problem solving technique

4. What is constraint satisfaction problem

5. What is unification algorithm

6. How can you represent the resolution in predicate logic

7. List out the advantages of non monotonic reasoning

8. Differentiate between JTMS and LTMS

9. What are framesets and instances

10. List out the important components of a script

Part –b

11. A) 

i) give an example of a problem for which breadth first search would work better than depth first search.

II) explain the algorithm for steepest hill climbing 

Or

b) explain the following search strategies 

i) best first search

ii) A* search

12. A) explain min-max search procedure

Or

b) describe alpha-beta pruning and give the other modifications to the minmax procedure to improve its performance.

13. A) illustrate the use of predicate logic to represent the knowledge with suitable example.

Or

b) consider the following sentences

• John likes all kinds of food

• Apples are food

• Chicken is food

• Anything anyone eats and isn’t killed by is food

• Bill eats peanuts and is still alive

• Sue eats everything bill eats

i) translate these sentences into formulas in predicate logic

ii) prove that john likes peanuts using backward chaining

iii) convert the formulas of a part into clause form 

iv) prove that john likes peanuts using resolution 

14. a) i) with an example the logics for non monotonic reasoning 

or

b) explain how Bayesian statistics provides reasoning under various kind s of uncertainty.

15). A) i) construct semantic net representations for the following .

• pomepeian (marcus), blacksmith(marcus)

• mary gave the green flowered vase to her favorite cousin.

ii)construct partitioned semantic net representations for the following :

• every batter hit a ball 

• all the batters like the pitcher 

Or

b). illustrate the learning from examples by induction with suitable example.