CSIT-504 (B) - Artificial Intelligence

Explain the terms f', g', h', open and closed in A* algorithm with suitable example.

Test whether the following production systems are commutative. Justify your answer.

i) Knowledge Base IF A & B Then C IF C Then D. IF A & D Then E. Initial wm ={A, B}

ii) Knowledge Base IF A & B Then C. if X & Y Then C. if A Then E if B Then F Initial wm ={A, B, X, Y}

Assume the following facts:

i) Steve only likes easy course

ii) Science courses are hard

iii) All the courses in the CSE department are easy

iv) CS301 is a CSE course Use resolution to answer the question "what course would steve like?"

Show that the following formula is valid: $(A(X) \lor B(Y)) \to C(Z) \Leftrightarrow (\neg A(X) \land \neg B(Y)) \lor C(Z)$ Where X, Y, Z are variables and A, B and C are predicates.

Show a conceptual dependency representation of the sentence. "John begged Mary for a pencil" How does this representation make it possible to the answer the question - "Did John talk to Mary"?

Construct partitioned semantic net representations for following:

i) Every batter hit a ball.

ii) All the batters like the pitcher.

For each of the sentences, show a parse tree.

i) John wanted to go to the movie with Sue.

ii) I heard the story listening to the radio.

Show the computation for the first 3 ply moves in a tac-tac-toe game using $\alpha$-$\beta$ cut off algorithm.

How learning in problem solving improve the performance?

Case based reasoning shares many of the same ideas of learning by analogy. Briefly describe how transformational and derivational analogy could apply in case based reasoning systems.

Consider the following knowledge base:

i) The-humidity-is-high $\lor$ the sky-is-cloudy

ii) If the-sky-is-cloudy then it-will-rain

iii) If the-humidity-is-high then it-is-hot.

iv) it-is-not-hot and the goal : it-will-rain. Prove by resolution theorem that the goal is derivable from the knowledge base.

What are the different stages of the expert system life cycles? Describe each stage.

A math teacher gave her class two tests. 25% of the class passed both test and 42% of the class passed first test. Using Bayesian theorem calculate the % of those who passed first test also passed in second test.

Define fuzzy logic with its various operations.

Forward and Backward Reasoning

AO* algorithm

Refutation and Resolution