MCA Fifth Semester Artificial Intelligence and Expert System Question Paper
Fifth Semester Examination- 2010
ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEM
Answer question No. 1 which is compulsory and any five from the rest.
The figures in the right-hand margin indicate marks.
1. Answer the following questions:- [2*10=20]
(a) Differentiate between performance measure and utility function.
(b) Explain why problem formulation must follow goal formulation.
(c) Prove that Breadth-first search is a special case of uniform-cost search.
(d) Define in your own word the terms constraint satisfaction problem.
(e) Explain the use of quantifiers in a First-order logic.
(f) Prove the completeness of resolution.
(g) Describe the difference and similarities between problem solving and planning.
(h) Describe how critical path method can be used to determine the possible start and end times of each action.
(i) Draw a decision tree for the problem of deciding whether to move forward at a road interaction given that the light has just turned green.
(j) Describe the advantage of chart parsing over top-down parsing method.
2. (a) Describe briefly the Local Seach algorithm. 
(b) Differentiate the local Seach algorithm with informed search strategies. 
3. (a) Describe the method of Alpha-Beta pruning with examples. 
(b) Write axioms describing the predicates Grandchild, Grandmother, Brother, Sister and daughter using First order logic. 
4. (a) How can resolution be used to show that a sentence is valid or unsatisfiable ? 
(b) Describe the planning graph for the spare time problem. 
5. (a) Explain the computational Learning Theory. 
(b) Differentiate between Explanation based learnig and Relevance based learning . 
6. (a) Trace the bottom up parse on the String "Every agent smells a wumpus". 
(b) Describe a grammar that can derive a parse tree and semantic interpretation for "Someone walked slowly to the Supermarket".
7. (a) What is an Expert System ? Draw the design of an Expert System. 
(b) Compare between the problem solving and expert system.
8. Write short notes on (any four): [2.5*4=10]
(a) Partial order planning
(c) Inductive learning
(d) Augmented grammar
(e) Bayesian network
(f) Ground Resolution Theorem
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