Code: AC20/AT21                                                    Subject: ARTIFICIAL INTELLIGENCE &

                                                                                                                   NEURAL NETWORKS

Time: 3 Hours                                                                                                     Max. Marks: 100

NOTE: There are 9 Questions in all.

· Question 1 is compulsory and carries 20 marks. Answer to Q. 1. must be written in the space provided for it in the answer book supplied and nowhere else.

· Out of the remaining EIGHT Questions answer any FIVE Questions. Each question carries 16 marks.

· Any required data not explicitly given, may be suitably assumed and stated.

Q.1       Choose the correct or best alternative in the following:                                         (2x10)

a. Which of the following verbs can be represented as MTRANS using Schank’s CD representation

(A)  walk                                             (B)  tell

(C)   give                                             (D)  run

b. Non monotonic reasoning deals with

(A) complete information                    (B)  incomplete information

(C)  an always growing fact base          (D)  none of the above

c. In the alpha-beta minimax search, alpha is _____________ on the values that a  __________ node maybe ultimately assigned.

(A) a lower bound, maximizing            (B)  an upper bound, minimizing

(C)  a lower bound, minimizing             (D)  an upper bound, maximizing

             d.   In connectionism, _____________ is a search technique and the learning techniques are _______________ and ___________.

(A)  Parallel relaxation, version spaces, A*.          

(B)  Parallel relaxation, explanation-based learning, and discovery.

(C)  Parallel relaxation, backpropogation, reinforcement learning.

(D)  Parallel relaxation, hill climbing, reinforcement learning.

             e.   The ID3 algorithm constructs decision trees by choosing

(A) Attributes that will yield more information       

(B) Attributes that will yield less information

(C) Attributes that will  not yield any information  

(D) None of the above

             f.    Generalisation hierarchy does not support property inheritance

(A) True                                              (B)  False

             g.   Resolution works on statements that are in single canonical form

(A) True                                             (B)  False

             h.   Natural deduction doesn’t use human theorem proving

(A) True                                             (B)  False

             i.    Unification is a process to represent substitutions during pattern matching

(A)  True                                             (B)  False

             j.    Bayesian networks uses more of local representation which describe clusters

(A)  True                                             (B)  False

Answer any FIVE Questions out of EIGHT Questions.

Each question carries 16 marks.

Q.2     a.   Discuss the significance of State space search in solving an AI problem.              (8)

             b.   What are the various search strategies known? Differentiate among them.            (8)

Q.3     a.   Symbolize and validate the following argument.

All law-abiding citizens pay their taxes.

                   Mr. Shyam pays his taxes.

                   Therefore, Mr. Shyam is a law-abiding citizen.                                                    (6)

             b.   Differentiate between AO* and A* algorithm.                                                   (10)

Q.4     a.   Let STACK(X,Y) and PICKUP(X) be two of the operators for manipulating blocks on a table using one arm of  a robot. Formulate the precondition, delete and add lists for these operators. These operators are to be used by a simple planner using a goal stack.

Suppose the goal to be achieved is ON(C,A) and ONTABLE(A) from the initial state ONTABLE(A) and ONTABLE(C). Explain the details of plan generation where the plan is PICKUP(C) followed by STACK(C,A).                                    (10)

b.   Explain Alpha-cut off and Beta-cut off with examples.                                         (6)

Q.5     a.   Discuss the various problems being faced by Expert System.                               (6)

             b.   Consider the following set of propositions

                                       patient has spots

                                       patient has measles

                                       patient has high fever

                                       patient has been inoculated against measles

                                       patient has an allergy

                   (i) Create a network that defines the casual connections among these nodes.

                   (ii) Make a Bayesian network by constructing the necessary conditional probability matrix.              (10)

  Q.6     a. Describe in general , clauses, facts, goals and rules of PROLOG. Elaborate them with respect to the knowledge given below.                      

                   “A house has a roof, a door and a window. A door has a knob. If an entity is a house, then it has a door. My house is  a house.”           (8)

             b.   Write a PROLOG program to find the maximum number from a given list of numbers.                    (8)

Q.7     a.   Describe the candidate elimination algorithm in narrowing the version space using an example.                                                                    (8)

b.   Explain the various components of a planning system.                                          (8)

Q.8           Write short notes on

(i) Non linear planning

(ii) Non Monotonic Reasoning

(iii) Characteristics of a production system

(iv) Activation functions of a Neuron.                                                       (4  4)

Q.9     a.   Consider the following sentence

John punched Bill.

(i) Show how it would be represented in case grammar.

(ii) Show how it would be represented using conceptual dependency graph.

(iii) Discuss the advantages and disadvantages of these representations.         (10)

             b.   Describe the different strategies that can be used for knowledge Acquisition.                       (6)