Artificial Intelligence - Dec 2015

Computer Engineering (Semester 7)

TOTAL MARKS: 80
TOTAL TIME: 3 HOURS (1) Question 1 is compulsory.
(2) Attempt any three from the remaining questions.
(3) Assume data if required.
(4) Figures to the right indicate full marks.

Attempt any four (4) questions from the following.

1 (a) Define heuristic function. Give an example heuristics function for Blocks World Problem.(5 marks) 1 (b) Find the the heuristics values for a particular state of the Blocks World Problem.(5 marks) 1 (c) Define Rationality and Rational Agent. Give an example of rational action performed by any intelligent agent.(5 marks) 1 (d) Compare and Contrast problem solving agent and planning agent.(5 marks) 1 (e) Represent the following statement into FOPL.
(i) Anyone who kills an animal is loved by no on.
(ii) A square is breezy if and only if there is pit in a neighbouring square (Assume the wumpus world environment).
(iii) Give the PEAS description for an Internet shopping agent. Characterize its environment.(5 marks) 2 (a) Consider the graph given in Figure 1 below. Assume that the-initial state is S and the goal state is 7. Find a path from the initial state to the goal state using A* Search. Also report the solution cost. The straight line distance heuristic estimates for the nodes are as follows: b(1)=14, h(2)=10, h(3)=8, h(4)=12, h(5)=10, h(6)=10, h(S)=15. (10 marks) 2 (b) Draw and describe the architecture of expert system.(6 marks) 2 (c) Convert the following propositional logic statement into CNF.(4 marks) 3 (a) Consider the following axioms:
All people who are graduating are happy.
All happy people smile.
Someone is graduating.
i) Represent these axioms in first order predicate logic.
ii) Convert each formula to clause form
iii) Prove that 'Is someone smiling?' using resolution technique. Draw the resolution tree.(12 marks) 3 (b) What are the basic building blocks of Learning Agent? Explain each of them with a neat block diagram.(8 marks) 4 (a) Construct a decision tree for the following set of samples. Write any two decision rules obtained from the tree. Classify a new sample with (gender = 'Female', height='1.92m')